This project applies Simple Linear Regression using Python to predict an employee's salary based on their years of experience. A real-world business dataset (Salary_Data) is used and analyzed using Pandas and visualized with Seaborn and Matplotlib. A scatter plot is created to visualize the relationship between experience and salary. The dataset is split into training (80%) and testing (20%) sets using train_test_split. A linear regression model is trained using Scikit-learn, and predictions are made on the test set. Model performance is evaluated using Mean Squared Error (MSE) and R² Score. The regression line is plotted over the data to visualize the best fit. A bar chart compares actual vs predicted salaries. The project also includes user input to predict salary based on custom experience. This demonstrates core skills in regression, data visualization, and performance evaluation.