With the continuous development of financial markets, silver futures trading has become increasingly significant in the investment sector. In recent years, the application of machine learning techniques in finance has provided novel perspectives for futures trading. This paper focuses on silver futures and proposes an effective trading strategy framework based on machine learning. The research proceeds through the following steps: Background Analysis, Model Selection, Model Training and Evaluation, and Strategy Implementation. Experimental results demonstrate that machine learning-based strategies can significantly enhance trading returns while mitigating risks. This research provides a reference framework for developing strategies in other financial derivatives markets.