A model for liquid-solid extruding process is established by introducing an artificial neural network into parameter sensitivity analysis during the liquid-solid extruding process. Sensitivity value at per sample point of the processing parameters can be obtained to quantitatively determine the sensitivity index under co-action of several uncertainty parameter conditions by mapping nonlinear network to resolve partial differential coefficient of output via input based on the model. The results show that the influencing orders on liquid-solid extruding process is infiltrating time

and then pouring temperature and mould temperature

and then infiltrating pressure

which are accordant with experimental ones.