One of the fundamental challenges in environmental studies and management is the unavailability of sufficient spatial data. To address this issue, various interpolation methods have been developed, with their accuracy being influenced by environmental factors, local conditions, and the parameters used in the data. Choice the optimal interpolation method is always a critical challenge. In this study, the optimization of the Cubic Spline interpolation method using fuzzy logic has been investigated. In proposed method, the elevation of points incorporated as fuzzy membership functions in the calculations. The accuracy of the proposed method (Fuzzy Cubic Spline) evaluated by comparing with ground elevation measurements and the results of the Spline interpolation method. The results indicate that the Fuzzy Cubic Spline interpolation method, with a correlation coefficient of 97.31%, performs better in estimating the Digital Elevation Model (DEM) compared to the Spline interpolation method, which has a correlation coefficient of 95.78%. Additionally, the RMSE values for the proposed method are lower than Spline interpolation method, significantly enhancing the accuracy of the DEM estimation.