This research aimed to analyze the impact that socioeconomic and urban vari- ables have on crime rates for Rio de Janeiro. To achieve that, we structured a dataset containing, for each neighborhood, the per capita crime rate for three dif- ferent categories of crimes (against passersby, stores, and vehicles), socioeconomic variables (regarding education, age, income, employment, and others), and urban variables (such as the number of industries, commerces, and public administration establishments). Then, we used those features to identify the hotspot neighbor- hoods for each crime type and studied possible counterfactuals for specific regions. We found that not only do the different crimes happen in different parts of the city (passerby crime hotspots concentrate in the South and North zones, the store ones in the South and Central zones, and the vehicle ones in the North zone) but also that the counterfactuals vary significantly depending on the analyzed neigh- borhood. We found, for example, that economic inequality and unemployment can be relevant factors for the passerby and store crimes in wealthier neighborhoods, while the lack of people movement is relevant for other neighborhoods regarding passerby crime.