Abstract: One essential part of automated diagnosis systems for SI engines is due to elements of air path system. The faults occur in this subsystem can result in deviation in air-fuel ratio, which causes increased emissions, misfire and especially loss of power and drivability problems. In this article, a model-based diagnosis system for air-path of an SI engine is developed. In addition, a nonlinear four-state dynamic model of an SI engine is utilized, and then the diagnosis system is designed in the framework of an Artificial Neural Network (ANN) classifier. Simulation results show that the constructed diagnosis system for seven fault modes considering all three kinds of common faults, including the manifold air temperature (MAT) sensor fault which comparatively less has been evaluated than other elements, is applied successfully. As another remarkable aspect of this work, all classes of faults are diagnosed in their full possible over reading (positive) and under reading (negative) ranges.