This paper presents a neural network-based disruption predictor wherein multiple plasma diagnostic signals are combined to provide a composite impending disruption warning indicator. To take into account that disruption precursors appear in different time instants for different pulses, an off-line clustering procedure allows to automatically select the training set samples.