A method for identification of mechanical parameters of an asynchronous motor is presented in this paper. The identification method is based on the use of our knowledge of the system. This paper clarifies the method by using the example identifying of mechanical parameters of the three-phase squirrel-cage asynchronous motor.A model of mechanical subsystem of the motor is presented as well as results of simulation. The special neural network is used as an identification model and its adaptation is based on the gradient descent method.The parameters of mechanical subsystem are derived from the values of synaptic weights of the neural identification model after its adaptation. Deviation of identified mechanical parameters in the case of moment inertia was up to 0.03% and in the case of load torque was 1.45% of real values.