Abstract: The relationship between the fundamental formability (tension, plane-strain, etc) and the simulant formability (deep-drawing, cupping, hole-expansion, fuki's cup) was studied by means of artificial neural network. Based on a lot of experimental data and the back-propagation algorithm, a B-P neural network model on the relationship was established. The variables of simulant formability of the sheet metal with known parameters of fundamental formability were predicted by computer. The predicted results are in good agreement with the experimental results. It is shown that artificial neural network is effective to study the simulant formability of the sheet metal.