Despite the purported benefits of occupant behavior (OB) models in simulating the effect of design factors on OB and vice versa, there are challenges associated with their use in building simulation practice due to the additional time and computational requirements. To this end, this article presents a method to incorporate these models in building performance simulations (BPS) as design-sensitive schedules. As an example demonstrating this method, more than 2,900 design alternatives of an office were generated by varying orientation, window to wall ratio (WWR), the optical characteristics of windows and blinds, and indoor surface reflectances. By using daylight simulations and stochastic OB modeling, unique light use schedules were generated for each design alternative. Two data-mining algorithms were then examined to identify the relationship between light use schedules and design parameters. Results indicated that WWR and building orientation had the strongest effect on light use schedules. These findings are relevant for building energy codes, as they provide an intermediate approach to incorporating design-sensitive schedules as BPS inputs. These design-sensitive schedules are expected to be superior to default ones currently specified in codes and standards, which ignore the effect of design factors on OB, and ultimately on energy consumption.