Computer Aided Engineering (CAE) models have proven themselves to be efficient surrogates of real-world systems in automotive industries and academia. To successfully integrate the CAE models into analysis process, model validation is necessarily required to assess the models’ predictive capabilities regarding their 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 the validation of CAE models. However, recent approaches for such application are commonly based on graphical comparison, while researches on the 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 surface 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 scores through a linear regression method. An analytical case is employed to verify the employed algorithms in the proposed method. Furthermore, the method is implemented on a real-world case involving surface comparison to show its potential in vehicle safety applications.