After categorizing offenses into different tiers based on their severity, my focus shifted to tier 3, which specifically encompasses crimes like larceny and robbery. To predict these tier 3 crimes, I conducted research to identify a suitable forecasting model. Opting for the ARIMA (AutoRegressive Integrated Moving Average) model, I found it to be a valuable tool in time series forecasting due to its simplicity, versatility, and effectiveness in capturing temporal patterns. The ARIMA model’s capability to handle a broad spectrum of time series data was a key factor in my decision. While I successfully implemented the ARIMA model, the results proved somewhat intricate, requiring further interpretation. Additionally, I plan to explore other models to determine which one yields the best outcomes.