diff --git a/src/main/kotlin/tribixbite/cleverkeys/BigramModel.kt b/src/main/kotlin/tribixbite/cleverkeys/BigramModel.kt
index 52cb1a31..41a1c06b 100644
--- a/src/main/kotlin/tribixbite/cleverkeys/BigramModel.kt
+++ b/src/main/kotlin/tribixbite/cleverkeys/BigramModel.kt
@@ -445,6 +445,46 @@ class BigramModel private constructor() {
         return min(max(multiplier, 0.1f), 10.0f)
     }
 
+    /**
+     * Get next word predictions based on previous word context.
+     * Returns words that are likely to follow the given context.
+     *
+     * @param context List of previous words (typically last 1-2 words)
+     * @param maxPredictions Maximum number of predictions to return
+     * @return List of (word, probability) pairs sorted by probability (descending)
+     */
+    fun getPredictedWords(context: List<String>?, maxPredictions: Int = 5): List<Pair<String, Float>> {
+        if (context.isNullOrEmpty()) {
+            // No context: return most common words from unigram model
+            val unigramProbs = languageUnigramProbs[currentLanguage] ?: languageUnigramProbs["en"]
+            return unigramProbs?.entries
+                ?.sortedByDescending { it.value }
+                ?.take(maxPredictions)
+                ?.map { Pair(it.key, it.value) }
+                ?: emptyList()
+        }
+
+        // Get the previous word (use the last word in context)
+        // Thread-safe: create local copy to avoid concurrent modification
+        val prevWord = context.lastOrNull()?.lowercase() ?: return emptyList()
+        
+        // Get language-specific bigram probabilities
+        val bigramProbs = languageBigramProbs[currentLanguage] ?: languageBigramProbs["en"]
+
+        // Find all bigrams that start with the previous word
+        val predictions = mutableListOf<Pair<String, Float>>()
+        
+        bigramProbs?.forEach { (bigramKey, prob) ->
+            val parts = bigramKey.split("|")
+            if (parts.size == 2 && parts[0] == prevWord) {
+                predictions.add(Pair(parts[1], prob))
+            }
+        }
+
+        // Sort by probability (descending) and take top N
+        return predictions.sortedByDescending { it.second }.take(maxPredictions)
+    }
+
     /**
      * Add a bigram observation (for user adaptation)
      */
diff --git a/src/main/kotlin/tribixbite/cleverkeys/SuggestionHandler.kt b/src/main/kotlin/tribixbite/cleverkeys/SuggestionHandler.kt
index a55aabd0..d59f7d46 100644
--- a/src/main/kotlin/tribixbite/cleverkeys/SuggestionHandler.kt
+++ b/src/main/kotlin/tribixbite/cleverkeys/SuggestionHandler.kt
@@ -50,6 +50,7 @@ class SuggestionHandler(
 ) {
     companion object {
         private const val TAG = "SuggestionHandler"
+        private const val SPACE_CHARACTER = " " // Trigger character for next word predictions
     }
 
     /**
@@ -572,7 +573,7 @@ class SuggestionHandler(
                     }
 
                     if (config.autocorrect_enabled && predictionCoordinator.getWordPredictor() != null &&
-                        text == " " && !inTermuxApp) {
+                        text == SPACE_CHARACTER && !inTermuxApp) {
                         val correctedWord = predictionCoordinator.getWordPredictor()?.autoCorrect(completedWord)
 
                         // If correction was made, replace the typed word
@@ -616,7 +617,14 @@ class SuggestionHandler(
                 // Reset current word
                 contextTracker.clearCurrentWord()
                 predictionCoordinator.getWordPredictor()?.reset()
-                suggestionBar?.clearSuggestions()
+                
+                // NEW: Show next word predictions after completing a word (space/punctuation)
+                // Only trigger for space character to avoid excessive predictions
+                if (text == SPACE_CHARACTER && config.word_prediction_enabled) {
+                    updateNextWordPredictions()
+                } else {
+                    suggestionBar?.clearSuggestions()
+                }
             }
             text.length > 1 -> {
                 // Multi-character input (paste, etc) - reset
@@ -698,6 +706,46 @@ class SuggestionHandler(
         }
     }
 
+    /**
+     * Update predictions for the next word based on context.
+     * Called after user completes a word (e.g., after typing space).
+     */
+    private fun updateNextWordPredictions() {
+        // Copy context to be thread-safe
+        val contextWords = contextTracker.getContextWords().toList()
+        
+        if (BuildConfig.ENABLE_VERBOSE_LOGGING) {
+            Log.d(TAG, "updateNextWordPredictions called with context: $contextWords")
+        }
+
+        // Cancel previous task if running
+        currentPredictionTask?.cancel(true)
+
+        // Submit new prediction task
+        currentPredictionTask = predictionExecutor.submit {
+            if (Thread.currentThread().isInterrupted) return@submit
+
+            // Get next word predictions (no partial word, only context)
+            val result = predictionCoordinator.getWordPredictor()?.predictNextWords(contextWords)
+
+            if (Thread.currentThread().isInterrupted || result == null || result.words.isEmpty()) {
+                return@submit
+            }
+
+            if (BuildConfig.ENABLE_VERBOSE_LOGGING) {
+                Log.d(TAG, "Next word predictions: ${result.words}")
+            }
+
+            // Post result to UI thread
+            suggestionBar?.post {
+                suggestionBar?.let { bar ->
+                    bar.setShowDebugScores(config.swipe_show_debug_scores)
+                    bar.setSuggestionsWithScores(result.words, result.scores)
+                }
+            }
+        }
+    }
+
     /**
      * Smart delete last word - deletes the last auto-inserted word or last typed word.
      * Handles edge cases to avoid deleting too much text.
diff --git a/src/main/kotlin/tribixbite/cleverkeys/WordPredictor.kt b/src/main/kotlin/tribixbite/cleverkeys/WordPredictor.kt
index baad74bc..ba88c9e1 100644
--- a/src/main/kotlin/tribixbite/cleverkeys/WordPredictor.kt
+++ b/src/main/kotlin/tribixbite/cleverkeys/WordPredictor.kt
@@ -28,6 +28,13 @@ class WordPredictor {
         private const val MAX_RECENT_WORDS = 20 // Keep last 20 words for language detection
         private const val PREFIX_INDEX_MAX_LENGTH = 3 // Index prefixes up to 3 chars
 
+        // Next word prediction scoring constants
+        private const val BIGRAM_SCORE_SCALE = 10000 // Scale bigram probability (0-1) to 0-10000 range
+        private const val FALLBACK_SCORE_MULTIPLIER = 0.5f // Multiplier for high-frequency words without bigram match
+        private const val PERSONALIZATION_BOOST_DIVISOR = 4.0f // Divisor for personalization boost (0-6 range → 1.0-2.5 multiplier)
+        private const val FREQUENCY_NORMALIZATION_FACTOR = 1000.0f // Normalization factor for frequency in scoring
+        private const val BIGRAM_EXPANSION_FACTOR = 3 // Get 3x more bigram candidates than requested for better filtering
+
         // Static flag to signal all WordPredictor instances need to reload custom/user/disabled words
         @Volatile
         private var needsReload = false
@@ -1175,6 +1182,124 @@ class WordPredictor {
         return dictionary.get().size
     }
 
+    /**
+     * Predict next words based on previous context (no partial word being typed).
+     * This is called after the user completes a word (e.g., after space/punctuation).
+     *
+     * Unlike predictInternal which completes a partial word, this predicts what
+     * word should come next based on the completed words in context.
+     *
+     * @param context List of previous completed words
+     * @param maxPredictions Maximum number of predictions to return (default 5)
+     * @return PredictionResult with next word predictions
+     */
+    fun predictNextWords(context: List<String>, maxPredictions: Int = 5): PredictionResult {
+        // OPTIMIZATION v3 (perftodos3.md): Use android.os.Trace for system-level profiling
+        android.os.Trace.beginSection("WordPredictor.predictNextWords")
+        try {
+            // Check if dictionary changes require reload
+            checkAndReload()
+
+            if (BuildConfig.ENABLE_VERBOSE_LOGGING) {
+                Log.d(TAG, "Predicting next words with context: $context")
+            }
+
+            val candidates = mutableListOf<WordCandidate>()
+
+            // Get bigram predictions from BigramModel
+            val bigramPredictions = bigramModel?.getPredictedWords(context, maxPredictions * BIGRAM_EXPANSION_FACTOR) ?: emptyList()
+
+            if (BuildConfig.ENABLE_VERBOSE_LOGGING) {
+                Log.d(TAG, "BigramModel returned ${bigramPredictions.size} predictions")
+            }
+
+            // Score each bigram prediction
+            for ((word, bigramProb) in bigramPredictions) {
+                // Skip disabled words
+                if (isWordDisabled(word)) {
+                    continue
+                }
+
+                // Check if word exists in dictionary
+                val frequency = dictionary.get()[word] ?: continue
+
+                // Calculate score combining bigram probability and frequency
+                // Bigram probability is 0-1, scale to 0-10000 range for scoring
+                val bigramScore = (bigramProb * BIGRAM_SCORE_SCALE).toInt()
+                
+                // User adaptation multiplier
+                val adaptationMultiplier = adaptationManager?.getAdaptationMultiplier(word) ?: 1.0f
+
+                // Dynamic context boost from learned N-gram patterns (ContextModel)
+                val contextAwareEnabled = config?.context_aware_predictions_enabled ?: true
+                val dynamicContextBoost = if (contextAwareEnabled && contextModel != null && context.isNotEmpty()) {
+                    contextModel?.getContextBoost(word, context) ?: 1.0f
+                } else {
+                    1.0f
+                }
+
+                // Personalization boost from user's typing frequency and recency
+                val personalizationEnabled = config?.personalized_learning_enabled ?: true
+                val personalizationMultiplier = if (personalizationEnabled && personalizationEngine != null) {
+                    val boost = personalizationEngine?.getPersonalizationBoost(word) ?: 0.0f
+                    1.0f + (boost / PERSONALIZATION_BOOST_DIVISOR)
+                } else {
+                    1.0f
+                }
+
+                // Combine all signals
+                // Bigram score is primary signal for next word prediction
+                // Frequency provides secondary ranking
+                val frequencyFactor = 1.0f + ln1p((frequency / FREQUENCY_NORMALIZATION_FACTOR).toDouble()).toFloat()
+                val finalScore = bigramScore * 
+                    adaptationMultiplier * 
+                    personalizationMultiplier *
+                    dynamicContextBoost *
+                    frequencyFactor
+
+                candidates.add(WordCandidate(word, finalScore.toInt()))
+            }
+
+            // If we don't have enough predictions from bigrams, add high-frequency words
+            if (candidates.size < maxPredictions) {
+                // Get most common words from dictionary that aren't already in candidates
+                val existingWords = candidates.map { it.word }.toSet()
+                
+                dictionary.get().entries
+                    .asSequence()
+                    .filter { !isWordDisabled(it.key) && !existingWords.contains(it.key) }
+                    .sortedByDescending { it.value }
+                    .take(maxPredictions - candidates.size)
+                    .forEach { (word, frequency) ->
+                        // Lower base score since these don't have context
+                        val adaptationMultiplier = adaptationManager?.getAdaptationMultiplier(word) ?: 1.0f
+                        val score = (frequency * FALLBACK_SCORE_MULTIPLIER * adaptationMultiplier).toInt()
+                        candidates.add(WordCandidate(word, score))
+                    }
+            }
+
+            // Sort by score and extract top N
+            candidates.sortByDescending { it.score }
+            
+            val predictions = mutableListOf<String>()
+            val scores = mutableListOf<Int>()
+
+            for (candidate in candidates.take(maxPredictions)) {
+                predictions.add(candidate.word)
+                scores.add(candidate.score)
+            }
+
+            if (BuildConfig.ENABLE_VERBOSE_LOGGING) {
+                Log.d(TAG, "Next word predictions (${predictions.size}): $predictions")
+                Log.d(TAG, "Scores: $scores")
+            }
+
+            return PredictionResult(predictions, scores)
+        } finally {
+            android.os.Trace.endSection()
+        }
+    }
+
     /**
      * Helper class to store word candidates with scores
      */
diff --git a/web_demo/swipe_vocabulary.json b/web_demo/swipe_vocabulary.json
index 44a137e4..ac6d4dc5 100644
--- a/web_demo/swipe_vocabulary.json
+++ b/web_demo/swipe_vocabulary.json
@@ -1,219332 +1,219332 @@
-{
-  "metadata": {
-    "total_words": 150252,
-    "common_words_count": 7002,
-    "length_distribution": {
-      "3": 7617,
-      "2": 671,
-      "4": 12175,
-      "5": 17661,
-      "6": 21921,
-      "7": 22446,
-      "9": 16363,
-      "10": 12123,
-      "8": 20185,
-      "11": 8021,
-      "13": 3036,
-      "12": 4959,
-      "14": 1546,
-      "15": 816,
-      "16": 380,
-      "18": 66,
-      "17": 203,
-      "19": 43,
-      "20": 20
-    },
-    "frequency_thresholds": {
-      "very_common": 1e-05,
-      "common": 1e-06,
-      "uncommon": 1e-07,
-      "rare": 1e-08
-    }
-  },
-  "word_frequencies": {
-    "the": 0.0537,
-    "to": 0.0269,
-    "and": 0.0257,
-    "of": 0.0251,
-    "in": 6.46e-08,
-    "is": 1.29e-06,
-    "for": 0.0102,
-    "that": 0.0102,
-    "you": 0.00955,
-    "it": 2.63e-08,
-    "on": 0.00813,
-    "with": 0.00708,
-    "this": 0.00661,
-    "was": 1.07e-07,
-    "be": 0.00617,
-    "as": 3.09e-06,
-    "are": 0.0055,
-    "have": 0.00513,
-    "at": 0.00501,
-    "he": 0.0049,
-    "not": 0.0049,
-    "by": 0.00457,
-    "but": 0.00427,
-    "from": 0.00427,
-    "my": 0.00372,
-    "or": 2.45e-08,
-    "we": 0.00347,
-    "an": 0.00339,
-    "your": 1.95e-07,
-    "all": 0.00331,
-    "so": 0.00331,
-    "his": 4.37e-08,
-    "they": 0.00316,
-    "me": 0.00302,
-    "if": 1.51e-08,
-    "one": 0.00295,
-    "can": 0.00288,
-    "will": 0.00282,
-    "just": 0.00269,
-    "like": 0.00257,
-    "about": 0.00251,
-    "up": 0.00245,
-    "out": 0.0024,
-    "what": 0.0024,
-    "has": 1.29e-07,
-    "when": 0.00234,
-    "more": 0.00229,
-    "do": 0.00224,
-    "no": 0.00224,
-    "were": 0.000251,
-    "who": 0.00219,
-    "had": 0.00214,
-    "its": 8.51e-08,
-    "their": 0.00214,
-    "there": 6.03e-08,
-    "her": 0.002,
-    "which": 0.002,
-    "time": 0.00195,
-    "get": 0.00191,
-    "been": 0.00186,
-    "would": 0.00186,
-    "she": 0.00182,
-    "new": 0.00178,
-    "people": 0.00178,
-    "how": 0.00174,
-    "dont": 2.29e-08,
-    "some": 0.00158,
-    "also": 0.00155,
-    "them": 0.00155,
-    "now": 0.00151,
-    "other": 0.00145,
-    "im": 4.9e-05,
-    "our": 0.00138,
-    "than": 0.00135,
-    "good": 0.00132,
-    "only": 0.00132,
-    "after": 0.00129,
-    "first": 0.00129,
-    "him": 0.00129,
-    "into": 0.00129,
-    "know": 0.00126,
-    "see": 0.00126,
-    "two": 0.00126,
-    "make": 0.0012,
-    "over": 0.0012,
-    "think": 0.0012,
-    "any": 0.00117,
-    "then": 0.00117,
-    "could": 0.00115,
-    "back": 0.0011,
-    "these": 0.0011,
-    "us": 3.39e-07,
-    "want": 2.57e-07,
-    "because": 0.00107,
-    "go": 0.00107,
-    "well": 7.76e-05,
-    "said": 0.00102,
-    "way": 0.00102,
-    "most": 0.001,
-    "much": 0.001,
-    "very": 0.001,
-    "where": 0.001,
-    "even": 0.000977,
-    "should": 0.000977,
-    "may": 0.000955,
-    "here": 0.000933,
-    "need": 0.000933,
-    "really": 0.000933,
-    "did": 0.000912,
-    "right": 0.000912,
-    "work": 0.000912,
-    "year": 0.000912,
-    "years": 2.4e-05,
-    "being": 0.000891,
-    "day": 0.000891,
-    "too": 0.000891,
-    "going": 0.000871,
-    "before": 0.000851,
-    "off": 0.000851,
-    "why": 0.000851,
-    "made": 0.000832,
-    "still": 0.000832,
-    "take": 0.000832,
-    "got": 0.000813,
-    "many": 0.000813,
-    "never": 0.000813,
-    "those": 0.000794,
-    "life": 0.000776,
-    "say": 0.000776,
-    "world": 0.000776,
-    "down": 0.000759,
-    "great": 0.000759,
-    "through": 0.000741,
-    "youre": 1.15e-07,
-    "last": 0.000724,
-    "thats": 3.31e-05,
-    "while": 0.000724,
-    "best": 0.000692,
-    "such": 0.000692,
-    "love": 0.000661,
-    "man": 0.000661,
-    "home": 0.000646,
-    "long": 0.000646,
-    "look": 0.000646,
-    "something": 0.000646,
-    "use": 0.000646,
-    "cant": 2.24e-05,
-    "same": 0.000631,
-    "used": 0.000631,
-    "both": 0.000617,
-    "every": 0.000617,
-    "am": 1.32e-08,
-    "come": 0.000603,
-    "part": 0.000603,
-    "state": 0.000603,
-    "three": 0.000603,
-    "around": 0.000589,
-    "between": 0.000589,
-    "always": 1.48e-08,
-    "better": 0.000575,
-    "find": 0.000575,
-    "help": 0.000562,
-    "high": 0.000562,
-    "little": 0.000562,
-    "old": 0.000562,
-    "since": 0.000562,
-    "another": 0.00055,
-    "does": 2.14e-07,
-    "own": 0.00055,
-    "things": 6.76e-07,
-    "under": 0.000537,
-    "during": 0.000525,
-    "game": 0.000525,
-    "ive": 1.05e-05,
-    "thing": 0.000525,
-    "give": 0.000513,
-    "house": 0.000513,
-    "place": 0.000513,
-    "school": 0.000513,
-    "again": 0.000501,
-    "next": 0.000501,
-    "each": 0.00049,
-    "mr": 0.00049,
-    "without": 0.00049,
-    "against": 0.000479,
-    "didnt": 9.77e-08,
-    "end": 0.000479,
-    "found": 0.000479,
-    "must": 0.000479,
-    "show": 0.000479,
-    "big": 0.000468,
-    "feel": 0.000468,
-    "sure": 0.000468,
-    "team": 0.000468,
-    "ever": 0.000457,
-    "family": 0.000457,
-    "keep": 0.000457,
-    "might": 0.000457,
-    "please": 0.000457,
-    "put": 0.000457,
-    "money": 0.000437,
-    "free": 0.000427,
-    "second": 0.000427,
-    "someone": 0.000427,
-    "away": 0.000417,
-    "left": 0.000417,
-    "number": 0.000417,
-    "city": 0.000407,
-    "days": 5.89e-06,
-    "lot": 0.000407,
-    "name": 0.000407,
-    "night": 0.000407,
-    "play": 0.000407,
-    "until": 0.000407,
-    "company": 0.000398,
-    "doing": 0.000398,
-    "few": 0.000398,
-    "hes": 9.12e-06,
-    "let": 0.000398,
-    "real": 0.000398,
-    "called": 0.000389,
-    "different": 0.000389,
-    "having": 0.000389,
-    "set": 0.000389,
-    "thought": 0.000389,
-    "done": 0.00038,
-    "however": 0.00038,
-    "getting": 0.000372,
-    "god": 0.000372,
-    "government": 0.000372,
-    "group": 0.000372,
-    "looking": 0.000372,
-    "public": 0.000372,
-    "top": 0.000372,
-    "women": 0.000372,
-    "business": 0.000363,
-    "care": 0.000363,
-    "start": 0.000363,
-    "system": 0.000363,
-    "times": 1.58e-06,
-    "week": 0.000363,
-    "already": 0.000355,
-    "anything": 0.000355,
-    "case": 0.000355,
-    "nothing": 0.000355,
-    "person": 0.000355,
-    "today": 0.000355,
-    "change": 1.26e-07,
-    "enough": 0.000347,
-    "everything": 0.000347,
-    "full": 0.000347,
-    "live": 0.000347,
-    "making": 0.000347,
-    "point": 0.000347,
-    "read": 0.000347,
-    "theres": 7.94e-06,
-    "told": 0.000347,
-    "yet": 0.000347,
-    "bad": 0.000339,
-    "doesnt": 5.75e-08,
-    "four": 0.000339,
-    "hard": 0.000339,
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-    "tell": 0.000339,
-    "including": 0.000331,
-    "music": 0.000331,
-    "power": 0.000331,
-    "seen": 0.000331,
-    "states": 1.12e-05,
-    "stop": 0.000331,
-    "water": 0.000331,
-    "based": 0.000324,
-    "believe": 0.000324,
-    "call": 0.000324,
-    "head": 0.000324,
-    "men": 0.000324,
-    "national": 0.000324,
-    "small": 0.000324,
-    "took": 0.000324,
-    "white": 0.000324,
-    "came": 0.000316,
-    "far": 0.000316,
-    "job": 0.000316,
-    "side": 0.000316,
-    "though": 0.000316,
-    "try": 0.000316,
-    "went": 0.000316,
-    "yes": 9.55e-08,
-    "actually": 0.000309,
-    "american": 0.000309,
-    "later": 0.000309,
-    "less": 2.04e-08,
-    "line": 0.000309,
-    "order": 0.000309,
-    "party": 0.000309,
-    "run": 0.000309,
-    "says": 1.7e-07,
-    "service": 0.000309,
-    "country": 0.000302,
-    "open": 0.000302,
-    "season": 0.000302,
-    "shit": 0.000302,
-    "thank": 0.000302,
-    "children": 0.000295,
-    "everyone": 0.000295,
-    "general": 0.000295,
-    "theyre": 3.09e-06,
-    "trying": 0.000295,
-    "united": 0.000295,
-    "using": 0.000295,
-    "area": 0.000288,
-    "black": 0.000288,
-    "following": 0.000288,
-    "law": 0.000288,
-    "makes": 0.000288,
-    "together": 0.000288,
-    "war": 0.000288,
-    "whole": 0.000288,
-    "car": 0.000282,
-    "face": 0.000282,
-    "five": 0.000282,
-    "kind": 0.000282,
-    "maybe": 0.000282,
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 }
\ No newline at end of file