Objective: The simulation and prediction model between the process of silk making and the quality of finished tobacco was established. Methods: The average influence value method was used to screen the process parameters in the process of making silk, and then a simulation model of the key process parameters of the silk and the quality of the final tobacco was constructed through the Back-Propagation neural network. Results: Comparing the simulated data with the measured data, the average relative error of the simulated prediction of the filling value was 3.16%; the average relative error of the simulated prediction of the whole cut rate was 0.67%; the average relative error of the simulated prediction of the broken cut rate was 5.33%. Conclusions: The relative error between the data predicted by this model and the real data is small, and the accuracy is high, which provides a theoretical basis and simulation method for the optimization of process parameters in the tobacco process.