Sales is very important factor in business. Supply and demand is mainly liable on the sales forecasting. The research is based on extracting critical information to support strategic decisions through data science approaches. This research work was carried out by gathering and preparing a large amount of sales data, where analysis was carried out in solving data quality concerns and producing a cleaned dataset. Our analysis and findings promises the business the most crucial information about the factors that affects consumer behavior, sales success, and regional differences. These insights are made available to stakeholders promoting data-driven decision-making. The sales forecasting is done using Machine Learning Algorithms and Time series. We Propose a robust and adaptable framework that empowers businesses to make data-driven decisions and achieve better accuracy in predicting sales demand