Passive Houses are characterized mainly by construction concepts that greatly reduce energy usage during the winter, but that can lead to significant overheating during the hotter summer days. Since in the Passive House concept thermal comfort during the summer mainly relies on natural ventilation to provide indoor cooling, the importance of airflow modeling tools for overheating prediction needs to be investigated. This research analyzes the effect of simplifications commonly made in airflow modeling techniques on the overheating assessment of Passive Houses by collecting measured data and calibrating a thermal model with a Passive House case study. Utilizing the calibrated model, a standalone Building Energy Model (BEM), BEM coupled with an Airflow Network Model (AFN), and BEM coupled with an AFN supported by the wind pressure coefficient values obtained from Computational Fluid Dynamics (CFD) simulation were created. The outcome of each modeling approach was then compared against each other. Results showed that the default infiltration and natural ventilation input values commonly utilized in literature, when compared to those obtained from either the AFN or AFN+CFD, are significantly overestimating the natural ventilation potential of Passive House buildings, resulting in a lower number of overheating hours (39.9% decrease) and inaccurate overheating evaluation outcomes. Therefore, the paper concludes that the use of at least an AFN is necessary when estimating the overheating hours of Passive Houses.