A Supermarket's profit is the money it earns when its total revenue exceeds its whole expenses. Any profit made by a corporation goes to its owners, who can choose to distribute it to shareholders as income or reinvest it in the business to fund future growth. The goal of this study is to analyze how the profitability of a particular superstore in the United States is affected by several economic factors. The multiple linear regression method, which is a statistical tool for prediction, will be utilized extensively throughout the paper. This project will go through data wrangling techniques, where this paper checked for inconsistency, missing values, and duplicate records, and filtered noisy data by identifying outliers and removing them, sampling the data due to its size to a more convenient size for ease of analysis, to proceeding to visualization, in order to determine what the results of the analysis are. Our primary method of multiple linear regression yielded an R-squared value of 0.563 for our model. This value represented the coefficient that indicated how well the values fit compared to the originally used values. Each one of the analyses that was carried out will be based on a confidence interval of 95%. In conclusion of the study, this paper found out that the more the sales and higher the quality the more chances of getting profit on the sales made with discount accounting to a negative variation to the profit sales. This model can be used to demonstrate future trends in profit margins and be applicable apply to other supermarkets to avoid losses.