This project predicts the Remaining Useful Life of aircraft engines using the NASA C-MAPSS dataset. Multiple machine learning and deep learning models (Linear Regression, Random Forest, SVR, and CNN+LSTM) are compared for time-series sensor data, with emphasis on feature engineering and real-world predictive maintenance applications.