The rapid growth of e-commerce has led to an increasing need for understanding and predicting consumer behavior. Machine learning (ML) techniques have emerged as powerful tools for analyzing large datasets and extracting meaningful insights. This paper explores the implementation of various machine learning techniques to predict consumer behavior in e-commerce, focusing oncustomersegmentation,purchaseprediction,a nd personalized recommendations. We discuss the methodologies, challenges, and potential applications of these techniques, providing a comprehensive overview of their effectiveness in enhancing e-commerce strategies