Abstract: A bridge fault modeling and simulation apparatus including a neural network simulates the effects of bridge defects in complementary metal oxide semiconductor integrated circuits. The apparatus includes a multilayer feedforward neural network (MLFN), implemented within the framework of a very high speed integrated circuit hardware description language (VHDL) saboteur. The saboteur is placed between logic cells in the IC simulation. The apparatus computes exact bridged node voltages and propagation delay times with due attention to surrounding circuit elements. It results in faster simulation and achieves excellent accuracy.