In this project, I developed machine learning models to forecast sales using a variety of algorithms, including Linear Regression, Random Forest Regressor, XGBoost Regressor and LSTM-based reinforcement learning. Trained and evaluated these models using sales data from 10 retail stores, assessing performance with metrics such as mean squared error, mean absolute error and R2 score. This analysis helps businesses forecast sales trends and make strategic budget decisions while offering flexibility for further optimization.