Inversion of gravity data is usually divided into two categories: linear and nonlinear inversion. Gravity data inversion processes are generally time-consuming due to their iterative, Ill-posed and Non-uniqueness processes. This paper introduces 3D Cross-Correlation for modelling of gravity anomaly and its vertical gradient (VGG) data which is a very fast method for modelling of these data in probability space. In this method first the earth is segmented into a 3D regular grid, after computing the correlation value for each node of the grid, these values are plotted. The areas with highest values are the most probable sites for buried anomalous masses. It should be noted that the results are in the range of [-1, +1], indicating an increase or decrease in the density of the anomalous mass relative to the host’s density. This method was applied to 2 synthetic models. The results show acceptable accuracy of this method in depth estimation and expansion of buried mass. After this method is verified and validated, it will be applied to the Shavvaz mine’s gravity anomaly data of Yazd, Iran and the results will be discussed.