Artificial neural network (ANN) is widely applied to the modeling of complex
systems, which has become a common modeling method in the study of materials science. As
the ideal candidates for high temperature structural materials, carbon materials are no doubt
involved in fatigue loads, so the study on forecasting fatigue life is meaningful. In this paper, the
electrical resistance at various fatigue cycles and level of applied stress of the materials under
tensile fatigue loading has been detected, and regarded the fracture or fatigue cycles equal to 106
as fatigue life of carbon materials. On the basis of the electrical resistance value, the fatigue life
has been forecasted by applied the ANN. The results indicated that the ANN could forecast the
fatigue life of carbon materials well; finally, the applications of ANN in the study of material,
such as properties prediction, damage prediction and failure detection were reviewed.