diff --git a/NDV_Code_By_VinayEsnapuram_Real_Estate/real_estate.py b/NDV_Code_By_VinayEsnapuram_Real_Estate/real_estate.py
new file mode 100644
index 000000000..4a0093e35
--- /dev/null
+++ b/NDV_Code_By_VinayEsnapuram_Real_Estate/real_estate.py
@@ -0,0 +1,87 @@
+
+
+
+ Real Estate Price Predictor
+
+
+
+
+ 🏠 Real Estate Price Estimator
+
+
+ {% if predicted_price %}
+ Estimated Price: {{ predicted_price }}
+ {% endif %}
+
+
+
+
+
+app.js
+
+from flask import Flask, render_template, request
+import joblib
+import numpy as np
+import pandas as pd
+
+app = Flask(__name__)
+
+# Load trained model and scaler
+model = joblib.load('model.pkl')
+scaler = joblib.load('scaler.pkl')
+
+@app.route('/')
+def home():
+ return render_template('index.html')
+
+@app.route('/predict', methods=['POST'])
+def predict():
+ area = float(request.form['area'])
+ bhk = int(request.form['bhk'])
+ age = int(request.form['age'])
+
+ input_df = pd.DataFrame([[area, bhk, age]], columns=['area', 'bhk', 'age'])
+ input_scaled = scaler.transform(input_df)
+ prediction = model.predict(input_scaled)[0]
+ price_lakhs = prediction / 100000
+
+ return render_template('index.html', predicted_price=f"₹{price_lakhs:,.2f} Lakhs")
+
+if __name__ == '__main__':
+ app.run(debug=True)