Understanding the spatial structure of urban environments is essential for identifying conditions that facilitate or deter property crimes. This study assessed visual connectivity at property crime hotspots (PCHs) in Nashik City, India. Property crime data, including robberies, burglaries, and thefts, were obtained from the Nashik City Police Department, while building footprint data were sourced from Google Open Buildings. Using QGIS, property crime locations were mapped, and hotspot areas were identified. Neighborhood layouts were then developed around these hotspots, and Visibility Graph Analysis (VGA) was performed in depthmapX to assess visual connectivity within 50-meter buffers of property crime locations. The analysis revealed spatial variations in visual connectivity across different PCHs, highlighting how the spatial configuration of neighborhoods influences surveillance and creates opportunities for property crimes. Areas with lower visual connectivity often corresponded to more property crimes, suggesting that restricted visibility due to compact spatial layouts may provide favorable conditions for property crime incidents. Conversely, locations with higher visual connectivity demonstrated fewer property crimes, indicating the positive influence of natural surveillance. The findings underscore the potential of space syntax-based visual analysis as a diagnostic tool for property crime prevention. By integrating spatial configuration analysis of neighborhoods with property crime mapping, this study provides a methodological framework for urban planners and urban designers to identify vulnerable areas and design interventions that enhance street visibility, spatial integration, and safety in urban neighborhoods.