<p>Mapping crime hotspots is an important technique for identifying areas with significant criminal activity. Law enforcement agencies must have access to timely and reliable information in order to plan and make sound decisions. Geographical Information Systems (GIS) offer a comprehensive approach to evaluating crime patterns by examining the locations and timing of incidences. Traditionally, crime mapping depended on pin-maps, which were often slow and inaccurate. This study aims to identify hotspots for hit-and-run incidents in six major districts of Maharashtra, India, during July and August 2023. The study used advanced geospatial approaches such as Kernel Density Estimation and Spatial Autocorrelation to identify substantial clusters of hit-and-run incidents. These hotspots were primarily found in densely populated urban areas, particularly the central business district and main highways. The statistics showed that high-traffic areas had a 25% greater frequency of incidents than less congested areas. A proximity-based spatial co-location (approximately 20%) was observed between liquor stores and hit-and-run events. These findings imply that strategic efforts, such as better urban planning and more traffic monitoring in specific hotspots, could considerably lower the occurrence of such crimes. The use of GIS in this study provided extensive insights into the spatial distribution of hit-and-run episodes, which laid the framework for future crime prevention initiatives.</p>