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The problem of NVH CAE model correlation in light of test and product variation has been addressed. An objective metric based on statistical hypothesis testing has been proposed and evaluated. This technique has been shown to work for frequency response functions. The hypothesis test answers the question ‘Are the involved frequency response functions statistically different than those in a reference set?’ This paper demonstrates that vehicles are uniquely identifiable by their frequency response functions. Under certain restrictive assumptions, the average gross error normalized by the ensemble variance is chi-squared distributed. Using a chi-squared test, the probability that a NVH CAE prediction is a member of a reference (test) set can be estimated. Within the context of a reference (test) set, this metric represents the limit to predictability. The metric was applied to examples including two midsize car NVH CAE models.