A tool was developed that allows evaluation of thermal mass control strategies using HVAC utility costs as the baseline for comparison. Inverse models are used to represent the behavior of the building, cooling plant, and air distribution system. Inverse models use measured data to “learn” system behavior and provide relatively accurate site-specific performance predictions. Based on weather and solar inputs, as well as occupancy and internal gains schedules and utility rates, the evaluation tool predicts the total HVAC utility cost for a specified control strategy. Intelligent thermal mass control strategies can then be identified in a simulation environment using this analysis tool. The evaluation tool was validated using data collected from a field site located near Chicago, Illinois. The tool predicted HVAC utility costs for a summer month billing period that were within approximately 5% of actual costs. Additional studies were performed to examine the utility savings potential for summertime operations at the field site using various thermal mass control strategies. The best strategy resulted in approximately a 40% reduction in total cooling costs as compared with night setup control. Simulation studies were also used to analyze the overall impact of location on the savings potential for use of building thermal mass. Representative utility rates for five locations (Boston, Chicago, Miami, Phoenix, and Seattle) were used along with the models obtained for the field site. Significant savings were achieved in all locations except Seattle.