As much of the world gears toward developing energy efficient and healthy buildings, natural ventilation is becoming an important aspect of building design. While ventilation driven by the stack effect is relatively simple to predict for many different building geometries, the prediction of wind-driven natural ventilation is far more complex due to ever-changing wind speed and direction. Currently, building designs utilizing wind-driven ventilation can only rely on roughly estimated airflow behaviors. In this study, we used full-scale experimental data and computational fluid dynamics (CFD) with the two equation turbulence model and fluctuating pressure boundary conditions to determine the accuracy of this standard turbulence model in analyses of cross-ventilation airflow. Experimental data for wind induced airflow was obtained by consistently measuring airflow characteristics inside and outside of a test house. The measured facade pressures were then used as the unsteady boundary conditions for the indoor CFD airflow model. The CFD results were then compared with the experimental data to determine whether the prediction was accurate. The preliminary finding of this study suggests that even with unsteady winds, time-varying pressure boundary conditions can be used to model and predict complex wind driven indoor airflow characteristics using CFD. This method can be helpful to engineers in assessing potential for natural ventilation as well as in designing an appropriate system for a proposed building.