Abstract: Based on feed forward multi-layer artificial neural network, a new way to estimate the friction factor between roller and workpiece was studied. The factor was taken as a multi-variable non-linear function which was affected jointly by such independent parameters as rolling temperature, lubricant viscosity and rolling speed. The nonlinear mapping of artificial neural network was used to construct a complicated mathematical model in terms of dynamic friction factor and influencing parameters. An interpolation-approximation method based on ANN was proposed and programmed to estimate the working friction factor in rolling process, with a simulation done as an example. The results showed that the new method provides a means available to control and stabilize effectively the rolling process without slippage and prevent it from unbalanced load.