The exploration and mining process, from grass-roots exploration to mine-site development is a multidisciplinary task and involves the collection, integration and analysis of datasets from many different sources. Geographic information Systems (GIS) have been used to coordinate and manage the large amounts of spatial and related nonspatial data associated with modem exploration programs. Once suitably captured in a GIS, these spatial data can be queried, analysed, and by the application of various techniques, maps that depict mineralisation potential or prospectivity, can be defined. Methodologies for the construction of prospectivity maps can be split into two complementary types: empirical and conceptual. Empirical methodologies analyse for spatial relationships between known deposits and surrounding features. Identified spatial relationships are quantified and ultimately integrated into a single map which highlights areas similar to those known to contain significant mineralisation. Conceptual methodologies, which are suited to areas that contain few known deposits, use current knowledge about the orebody formation to identify those areas which are most likely to contain significant mineralisation. This paper focuses on the use of a GIS for the analysis of geological exploration datasets and the construction of prospectivity maps using both empirical and conceptual methodologies.