As energy demand grows, climate change threatens to undermine adequate levels of indoor environmental quality (IEQ) in residential buildings. Urban Building Energy Models (UBEM) play a crucial role in assessing energy consumption, but their capability to evaluate thermal comfort remains limited. This paper analyzes two modeling approaches—Resistance-Capacitance (RC) models and Large-Scale (LS) simulations automated from GIS/CityGML to generate TRNSYS files—to assess their suitability for thermal comfort analysis in UBEM workflows. While RC models offer computational efficiency and simplified parameterization, they rely on air temperature approximations, limiting accuracy in complex buildings. LS models provide detailed multi-zone simulations, incorporating solar gains and occupant behavior, yet demand higher computational resources and model preparation efforts. A qualitative SWOT analysis highlights the strengths and limitations of both methodologies regarding computational cost, zoning capabilities, and thermal comfort indicators. Results indicate that both methods can estimate adaptive comfort and heat index, but the choice depends on accuracy requirements and computational constraints.