Criminal analysis and prediction using machine learning focuses on leveraging advanced computational techniques to identify patterns, trends, and potential criminal behavior from historical crime data. By applying algorithms such as classification, clustering, and predictive modeling, researchers can detect crime hotspots, forecast criminal activities, and even anticipate recidivism. This field integrates data from diverse sources—including police records, social media, and surveillance systems—to build intelligent models that support law enforcement in decision-making, resource allocation, and preventive strategies. With the growing availability of big data and real-time information, machine learning-driven criminal analysis offers the potential to enhance public safety, optimize investigative processes, and provide actionable insights while addressing challenges related to data privacy and ethical considerations.