The difficulties, due to a lack of information about stage-by-stage axial-compressor performance, are analyzed. To overcome these issues, a three-layer back-propagation neural-network applied Leven berg-Marquardt algorithm is presented and discussed. The experimental data provided by manufacturers are used for the neural-network training. Through twice training, the compressor's performance map can be predicted. The results can be used for the development of an off-design model or overall dynamic simulation of the behaviour of a gas-turbine power-plant. (c) 2006 Elsevier Ltd. All rights reserved.