A Design for Six Sigma (DFSS) statistical approach is presented in this report to correlate a CFD cabin model with test results. The target is the volume-averaged hot-soak terminal temperature. The objective is to develop an effective correlation process for a simplified CFD cabin model so it can be used in practical design process. It is, however, not the objective in this report to develop the most accurate CFD cabin model that would be too expensive computationally at present to be used in routine design analysis.A 3-D CFD model of a vehicle cabin is the central part of the computer modeling in the development of automotive HVAC systems. Hot-soak terminal temperature is a thermal phenomenon in the cabin of a parked vehicle under the Sun when the overall heat transfer reaches equilibrium. It is often part of the simulation of HVAC system operation. The strategy in our design process is to use a simplified CFD cabin model correlated with available test results for rapid routine design analysis. However, we have not seen published report to demonstrate a systematic correlation process for a cabin model where thermal physics are rather complex.This report introduces a DFSS statistical approach to develop an approximation (metamodel) of the expensive computer simulation of hot-soak process, and to guide the selection of input variable values subsequently to correlate the CFD model with given test data. The core process demonstrates using a small sample of CFD simulations to develop this approximation that enables model correlation with minimum computational effort.Although the targeted parameter for correlation in this study is the hot-soak terminal temperature, the procedure outlined herein is valid for other modeling results and other types of CFD models than the cabin model.