With the rise of artificial intelligence (AI) and machine learning (ML), forensic investigations have seen remarkable advancements in uncovering complex criminal activities through data analysis. These technologies enable the extraction of critical insights from vast amounts of collected data, transforming how crimes are detected and analyzed. For example, hacking incidents involving smartphones and other smart devices can now be diagnosed by monitoring dynamic user data such as heart rate, blood pressure, and sleep patterns, allowing for real-time, noninvasive tracking of potential intrusions or anomalies in data processing. This chapter delves into the development of precise AI-enabled models designed to predict and analyze crime-related data gathered from crime scenes. By leveraging sophisticated algorithms, these models offer powerful tools to identify patterns, behaviors, and threats that traditional forensic techniques may overlook. The focus is on building robust systems that can process and interpret data efficiently, providing law enforcement agencies with real-time insights and improving overall crime detection and prevention efforts.