Statistical Energy Analysis (SEA) models are routinely being adopted in up-front automotive sound package design. SEA models serve two important functions. First they provide a means of assessing noise and vibration performance relative to absolute targets. Secondly, they are used to assess various alternative designs or changes required to meet targets. This paper addresses how to objectively evaluate both the absolute and relative predictive capability of SEA models. The absolute prediction is assessed using a hypothesis test to determine membership of the analytical prediction relative to a set of test data. The relative prediction is assessed using hardware-designed experiments to estimate design sensitivities. Both have been found useful to drive model improvement efforts. Being able to objectively document model capability also improves the credibility of SEA model predictions and the design information they deliver.