Various modeling approaches have been developed and applied to predict the heat and mass transfer phenomena within buildings. As the theoretical basis, these transfer phenomena play a significant role in the estimation and prediction of building load and energy consumption. In consideration of the complexity of the phenomena observed, the results expected, the parameters investigated, and the degree of accuracy required, these modeling approaches can be represented with three models: Multi-zone models, Zonal models, and Computational Fluid Dynamics (CFD) models. In the application of these models in building load and energy simulation, selecting an appropriate model is an essential step, which mainly depends on four factors, including the level of accuracy needed, the problem to be solved, the computational time and resources that can be affordable, as well as the level of experience the users have. The importance of utilizing an appropriate model, however, is usually ignored by designers, engineers, and researchers. Therefore, in this paper, a literature review is carried out including the basic theories and the development and application of these modeling approaches used in building load and energy simulations. The major objective of this paper is to give building designers and/or researchers a better understanding of the models used for building load estimation and energy simulation in order to provide a reference for them to select an appropriate model for their needs. The study primarily reveals that the use of zonal/CFD modeling approaches in building simulation still rests on the theory research stage, but these modeling approaches define the direction for future development in building load estimation and energy modeling. Compared to CFD models, which use large memory and computer resources, zonal models could be a more possible substitute for single-/multi-zone models in building energy simulation in consideration of the current development of computer techniques and the unpopularity of high performance computing.