This assignment investigates the application of a decision tree model in predicting stock market trends. It details the process of constructing the prototype, including data preparation and feature selection. The evaluation reveals that while the decision tree achieves decent accuracy, it faces limitations due to factors like company news, political events, and legal rulings. The assignment concludes by suggesting future research directions, emphasizing the need to incorporate additional training methods and consider aspects like company rumors, trading volume, and financial reports for improved stock price prediction.