Energy modeling is globally used during the design phase to estimate future building energy performance. Predictions obtained from common energy estimation software typically deviate from actual energy consumption levels. This discrepancy can mainly be attributed to the misrepresentation of the role that building occupants play in the energy estimation equation. Although occupants might have different and varying energy use characteristics over time, current energy estimation tools assume they are constant. This paper proposes a new agent-based approach to commercial building energy modeling by accounting for the diverse and dynamic energy consumption patterns among occupants, in addition to the potential changes in their energy use behavior attributable to their interactions with the building environment and with each other. The impact of an active modeling of occupancy is then illustrated in a case study of an office in a university building, where more than 25% variation in the predicted energy consumption was obtained when using the proposed method versus a traditional commonly used method with static occupancy parameters.