This project aims to construct a sophisticated regression model leveraging Python and machine learning techniques to accurately forecast property prices in Bangalore. By analyzing various features such as location, square footage,and amenities, the model will provide valuable insights for both buyers and sellers in the real estate market. Through data preprocessing, feature engineering, and model optimization, we seek to create a robust predictive tool that aids in decision-making and enhances transparency in property transactions. The project will involve gathering and cleaning real estate data, implementing regression algorithms, and evaluating model performance to ensure reliability and effectiveness.