This project focuses on forecasting solar power generation using advanced machine learning models, including XGBoost and Random Forest. The analysis highlights data cleaning, preprocessing, and feature engineering, with Random Forest achieving an R-squared score of 0.91, emphasizing radiation as the most significant predictor.