The project's main goal was to create an analytical service platform for forecasting crime, which can strengthen the ability to prevent and combat crime based on verifiable forecasts and optimize the use of available Police forces and resources. As in forecasting criminal events over time, future events are associated with a sequence of historical ones by time series of observational irregularly spaced data and other exogenous variables affecting crime, especially various factors related to the entire environment: natural, social, economic, legal, and political, to which the forecast is to affect crime level and structure. The development of sufficient crime threat data-based prediction models may require an appropriate combination of criminal event history, determining the risk level, and geographic data characterizing the areas for which the threat is predicted. The article presents the data-based methodology for crime forecasting system and exemplary operating results. The final evaluation was done to verify the forecasts obtained based on actual data for selected categories of crime, considering the optimization of the use of forces and resources and identify proposals for changes in the criminal policy.