This project aims to refine stock market predictions by integrating market data with company financials. It focuses on resolving data compatibility challenges and enhancing predictive accuracy through selective data integration. This project addresses the lack of comprehensive datasets that combine these two data types and the need for predictive models that can interpret this integrated data effectively. By focusing on this aspect of the problem, the project aims to make a meaningful contribution to the field of stock market prediction, demonstrating how the integration of market and financial data can lead to more accurate and actionable insights.