Commercial break and enters are of concern to Vancouver businesses. The proximity to rapid transit stations creates easy access to commercial buildings. This study investigates the impact of transit station proximity on crime rates, particularly focusing on the new Broadway Subway extension to the metro system. Grounded in environmental criminology theories, this research combines network analysis with machine learning and econometric methods to extract historical data and provide crime forecasts. This approach utilizes panel data to observe junctions over multiple years, then a double machine learning framework is applied to accurately measure the effect of transit station proximity on crime rates. These findings are used to forecast future crime occurrences in the neighbourhoods where the Broadway Subway extension will occur. This analysis also provides valuable insights for urban planning and public safety strategies.