Various disciplines, engineering, humanities, and other sciences require interpolating many parameters. Geostatistics, with its structural analysis step, is widely used for this purpose. Variography is the valuable step used to assess the correlation and dependence of the data. However, the wrong choice of the variogram model encounter all the predictive attended results. This article illustrates how the use of inappropriate variogram models can seriously conduct to a misleading of predicted results for such analysis. The influence of the selection of the semi-variogram model is highlighted and illustrated by thematic maps developed using three different models (Gaussian, spherical and exponential). To avoid such a drawback, a methodical approach to select the most suitable model, based on the calculation and analysis of the mean error (ME), the mean square error (MSE), the root of the square error mean (REQM), mean standard error (ESM) and root of mean standard error (REQSM), is proposed in the present research study. Such contribution could reduce the negative effects of the choice of variogram model on the interpolation operation using the kriging technique.