The Heat Balance Method (HBM) is used for estimating the heating and cooling loads encountered in a vehicle cabin. A load estimation model is proposed as a comprehensive standalone model which uses the cabin geometry and material properties as the inputs. The model is implemented in a computer code applicable to arbitrary driving conditions. Using a lumped-body approach for the cabin, the present model is capable of estimating the thermal loads for the simulation period in real-time.Typical materials and a simplified geometry of a specific hybrid electric vehicle are considered for parametric studies. Two different driving and ambient conditions are simulated to find the contribution and importance of each of the thermal load categories. The Supplemental Federal Test Procedure (SFTP) standard driving cycle is implemented in the simulations for two North American cities and the results are compared. It is concluded that a predictive algorithm can be devised according to the driving conditions, vehicle speed, orientation, and geographical location. By using this model, the pattern of upcoming changes in the comfort level can be predicted in real-time in order to intelligently reduce the overall AC power consumption while maintaining driver thermal comfort.