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The dominant paradigm for studying domestic violence has been to focus on individual and relationship characteristics. As rich as this literature is, it has, like much of earlier criminology, ignored the place-based nature of this crime. There is very little empirical study of the spatial distribution of the crime of domestic violence. However, like most other crime, domestic violence is not randomly distributed in a city. Instead it clusters, exhibiting both repeat pattern offenses and traditional hot spots. What remains an unknown are the characteristics of the environmental backcloth that contribute to areas of greater risk for domestic violence. It this exploratory study, the predictive analytics of Risk Terrain Modeling are leveraged to study the features of the environment that create a higher risk for domestic violence. Testing different features using the RTMDx tool, identified predictors will be used to develop a model based on the combination of retrospective incident data and features of the geo-social environment in order to prospectively identify areas of higher risk. The model will be vetted using "hold back" data and then tested evolving real time data.