Computer Aided Engineering (CAE) models have proven themselves to be efficient surrogates of real-world systems in automotive industries. For the successful implementation of CAE models as an integrated part of the current vehicle development process, model validation is necessarily required to assess their predictive capabilities regarding intended usage. In the context of model validation, quantitative comparison which considers specific measurements in real-world systems and corresponding simulations serves as a principal step in the assessment process. For applications such as side impact analysis, surface deformation is frequently regarded as a critical factor to be measured for validating the CAE models. However, recent approaches for such application are commonly based on graphical comparison, while researches on the development of quantitative metric for surface-surface comparison are rarely found. To deal with this problem, a validation metric, which combines the discrepancies measurements in magnitude and shape, is proposed to evaluate the inconsistence between two deformed surfaces. For magnitude error, an exploited 2-dimensional Dynamic Time Warping (2D-DTW) method is applied to address the mismatch in geometric features between two surfaces. Geometric features, say mean curvatures of surfaces, are extracted for shape comparison. For decision making, the original assessments are then transformed into a weighted score through a linear regression method. An analytical case is employed to illustrate the proposed method. Furthermore, the method is applied to a side impact case study to show its potential in vehicle safety applications.