The wear to orthogonal metals of NBR is the main cause of affecting the endurance of ESPCP. The rotational speed, load and temperature are main influence factors of the wear of 45 steel. The BP neural network model used in the forecast of the 45 steel wear volume was established. The 45 steel wear volume was obtained using friction and wear machine under different experimental parameters. The wear volumes of different experimental parameters were forecasted using BP neural network. The results indicate that it is feasible to forecast the rotational speed, load and temperature to 45 steel wear volume.