In this talk, I will provide a brief geological background to GIS-based mineral potential modeling and review some of the GIS-based spatial analyses techniques used for generating input data for modeling. I will then summarize various knowledge-driven and data-driven aproaches to mineral potential modeling, focussing on aritifical intelligence techniques including expert systems and machine learning algorithms. Finally I will discuss some real-world case studies on applications of machine learnign and expert systems to modeling the potential of various types mineral deposits.