Abstarct: The high costs of waste removal and the complexity of the Gandy gold mine deposit have led to significant risks when expanding operational areas baxsed solely on traditional geological methods. The eastern section of the site, known as Region Sixty, is recognized as a high-potential area that partially connects to the central pit in future expansions. Various exploration efforts have been conducted in this region using different methods. Given the high costs associated with drilling and the related risks, the application of modern data-driven methods, including the Random Forest algorithm, has been explored for predicting optimal drilling locations. In this study, geochemical, geological, and tectonic data from the Gandy gold area were utilized to create a desirable potential map and ultimately identify optimal drilling points using the Random Forest algorithm. The proposed two-dimensional model has successfully predicted potential locations for encountering mineral deposits with high accuracy. This approach not only provides better insight into the subsurface structure of the area but also enables more precise planning and greater efficiency in the extraction process.The present research aims to enhance economic productivity and reduce environmental impacts by minimizing unnecessary drilling. The application of the Random Forest method in mineral resource exploration represents an important step in the development of innovative technologies in the mining industry.