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In the mining industry, identifying new geographic locations that are favorable for mineral exploration is very important. However definitive prediction of such locations is not an easy task. In the recent years artificial neural networks have received much attention in this area. This paper uses a class of neural networks known as the polynomial neural network (PNN) to construct a model to correctly classify given location into deposit and barren areas. This model uses the geographic information systems (GIS) data of the location. The method is tested on the GIS data for the Kalgoorlie region of Western Australia.