The sales forecast is based on Big Mart sales for various outlets to adjust the business model to expected outcomes. The resulting data can then be used to prediction potential sales volumes for retailers such as Big Mart through various machine learning methods. The estimate of the system proposed should take account of price tag, outlet and outlet location. A number of networks use the various machine- learning algorithms, such as linear regression and decision tree algorithms, and XGBoost regressor, which offers an efficient prevision of Big Mart sales based on gradient. At last, hyperparameter tuning is used to help you to choose relevant hyperparameters that make the algorithm Shine and produce the highest accuracy.