Purpose: The current research examines the utility of risk terrain modeling (RTM) in developing an aggregate neighborhood risk of crime (ANROC) measure. RTM is often employed at the micro-place, forecasting future crime by street segment from attributes of the physical environment. Controlling for concentrated socioeconomic disadvantage and residential stability, we examine the ability of RTM to forecast neighborhood-level violent crime rates in Little Rock, Arkansas. Methods: Grounded in the extant literature and our knowledge of the area, we identified 14 risk factors expected to influence violent crimes. Once a RTM was constructed on 2013 violent crimes, the risk of crime per cell was averaged by neighborhood (Census tract), developing an aggregate neighborhood risk of crime measure. The ANROC measure was used to predict 2014 neighborhood violent crime rates. Results: This measure significantly increases the understanding of variation in neighborhood violent crime rates. The regression analyses indicated all three measures were significant predictors of neighborhood violent crime rates in Little Rock. Conclusions: The overall pattern of results supported our contention that the development of a macro- or neighborhood-level measure reflecting risk for criminal opportunities contributes substantively to the neighborhoods and crime literature.