Digital Twin Technology (DTT) has emerged as a transformative tool, bridging the physical and digital worlds to create highly accurate virtual replicas of real-world environments. Originally utilized in manufacturing and healthcare, DTT is now being explored in forensic science for crime scene analysis and evidence simulation. By integrating data from IoT sensors, drone footage, and environmental variables, DTT allows investigators to reconstruct events, test hypotheses, and present compelling visual evidence in court. Unlike traditional crime scene documentation methods, such as photographs and static 3D models, DTT enables real-time updates and interactive analysis, significantly enhancing forensic accuracy and reliability. This paper investigates the potential of DTT to revolutionize forensic science, particularly in crime scene reconstruction and evidence simulation. While the technology offers substantial benefits, its forensic application is still in the early stages, facing challenges related to data integration, computational demands, and legal admissibility. Addressing these issues requires interdisciplinary collaboration between forensic professionals, engineers, and legal experts to develop standardized protocols. The findings underscore the transformative role of DTT in forensic investigations and education, emphasizing the need for further research to refine its methodologies and expand its adoption in forensic science.