The goal of the study was to devise a low cost approach to identify homes in public housing with high levels of pesticide residues, including banned and restricted use pesticides (RUPs), to help determine optimal strategies to reduce household exposures. We collected environmental samples from 42 public housing apartments in Boston, Massachusetts in 2002 and 2003 and gathered pesticide use information, housing characteristics, and demographics. Focusing on 5 organophosphate and pyrethroid pesticides, we used classification and regression tree analysis (CART) to disaggregate the pesticide concentration data into homogenous sub samples according to home characteristics, which allowed us to identify households and associated networks impacted by the mismanagement of pesticides. The CART analysis demonstrated reasonable sensitivity and specificity for models with more extensive household information but generally poor performance using only information available without a home visit. Apartments with high concentrations of cyfluthrin, a pyrethroid, were more likely to be associated with Hispanic residents who resided in their current apartment for more than 5 years, which was consistent with documented pesticide usage patterns. We conclude that using CART as an exploratory technique to better understand the home characteristics associated with elevated pesticide levels, may be a viable approach for risk management in large multi-unit housing developments.