The integration of machine learning techniques into agile software development has shown potential in improving project outcomes. This paper explores the application of machine learning to enhance decision-making and project management in cross-cultural agile teams. Our objective is to identify specific machine learning strategies that can be effectively incorporated into agile processes to optimize performance and collaboration among diverse team members. The study utilizes a combination of qualitative and quantitative analyses, drawing on case studies from international software development projects. Our findings indicate that data-driven insights can significantly improve sprint planning, risk assessment, and task prioritization. Additionally, we observed enhanced communication and cultural understanding among team members, which contributed to the overall success of the projects. These results suggest that the strategic integration of machine learning can not only enhance technical aspects of software engineering but also foster improved interpersonal dynamics. We conclude that future research should focus on developing dedicated machine learning tools tailored to the nuances of agile methodologies, particularly in multicultural settings.