Spline-based approaches have been applied to inverse problems in several areas. If proper spline bases are chosen, dimension of the problem can be significantly reduced while increasing estimation accuracy and robustness of the inverse procedure. We proposed Multivariate Adaptive Regression Splines (MARS) based methods for the solution of the inverse electrocardiography (ECG) problem considering the temporal and spatial evolution of the epicardial potentials. Our model defines the spline functions in terms of spatial parameters based on the given epicardial surface geometry. Thus, any change in geometry can alter the constructed model for the purpose of obtaining an accurate estimate. In this study, we focused on the effects of the geometric model inaccuracies on the proposed MARS-based approach.