This study proposes a simple but novel and applicable approach to solve the problem of smoothing effect of ordinary kriging estimates. This approach is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the standard deviation of sample data with addition of the mean value of original samples to the results. It bears great potential to reproduce the histogram and semivariogram of the primary data. Actually, raw data are transformed into normal scores in order to avoid the asymmetry of ordinary kriging estimates. Thus ordinary kriging estimates are first rescaled using the transformation equation and then back-transformed into the original scale of measurement. To test the proposed procedure, stratified random samples have been drawn from an exhaustive data set. Corrected ordinary kriging estimates follow the semivariogram model and back-transformed values reproduce the sample histogram, while preserving local accuracy.