Driving safety of a vehicle is largely influenced by the damper and the tire. Developed in this research is a fault diagnosis algorithm for the two components so that the driver can be promptly informed when fault occurs in one or both of them. To this end, the damper and the tire were modeled using the neural network from their experimental data, and fault diagnosis was made using frequency responses of the damping force and the dynamic wheel force. The algorithm was tested via experiments, and it demonstrated successful diagnostic performance under various driving conditions.