Time series prediction for economic processes is a topic of increasing interest. In order to reduce stock-keeping costs, a proper forecast of the demand in the future is necessary. We use artificial neural networks for a short term forecast for the sale of articles in supermarkets. The nets are trained on the known sales volume of the past for an entire group of related products. Additional information like changing prices is also given to the net to improve the prediction quality. The net is trained on a window of inputs describing a fixed set of recent past states by the back-propagation algorithm.