Ensuring occupant comfort is critical in designing climate-resilient urban landscapes and sustainable digital built environments, especially in the context of densely populated cities like Dhaka, Bangladesh. This study offers a new framework by integrating Building Information Modeling (BIM), Agent-Based Modeling (ABM), and System Dynamics (SD) approaches to effectively represent the occupant comfort within the four individual landscapes located at the university campus in Dhaka, Bangladesh. Initially BIM tool (i.e., Revit 2025) was used to represent urban landscape data that includes both physical and non-physical infrastructure. In addition, ABM and SD models are mainly used to generate stochastic occupant comfort data within the selected four locations in urban landscapes. For the model validation purpose, a comprehensive dataset of 700 entries were collected through physical surveys conducted over a specified period, encompassing 14 key features within the selected location. These features include demographic information, building characteristics, thermal comfort, and environmental variables. The above comprehensive framework achieved acceptable performance while calculating CVRMSE and MSE as defined by the standard guidelines (i.e., ASHRAE). By integrating BIM with ABM and SD, the study provides a holistic framework to model and predict occupant comfort in urban landscapes, accounting for complex interactions between environmental conditions, building infrastructure, and human comfort. This study offers actionable insights for urban planners, architects, and policymakers, enabling the development of sustainable, climate-adaptive outdoor comfort environments. This research aligns with global trends toward sustainable development in digitally constructed environments, thereby contributing to the broader objectives of improving occupant well-being and addressing environmental concerns in urban settings.