Exposure to black carbon (BC) is associated with adverse health effects. Cooking and heating with solid fuels are the major contributors of indoor BC, whereas vehicular emissions are the major outdoor source. Home characteristics such ventilation filters can reduce indoor levels of airborne particles, including BC. In this study, we developed and validated a predictive model for indoor BC concentrations. To achieve this task, concentrations of indoor and outdoor BC were measured in homes in Cincinnati. Home characteristics that could potentially modify indoor levels of BC were documented. A linear mixed effect model was developed to predict indoor BC by using the measured outdoor BC concentrations and documented housing characteristics as predictors of indoor BC. After the model was developed, a cross validation algorithm was used to test the accuracy of the predictive model. Predicted indoor BC concentrations explained 77% of the variability in the measured indoor BC concentrations.