The vacuum drying technology was applied in this experiment to study vacuum drying characteristics ofZanthoxylum?bungeanumto improve the drying rate and achieve large-scale vacuum drying production. Under the conditions of temperature(50; 60; 70 ℃); vacuum(-0.06; -0.04; -0.02 MPa); and loading(30; 40; 50 g) comprehensive tests; the effects of three factors on total drying time and drying rate ofZanthoxylum?bungeanumwere investigated. Seven different drying models were used to simulate the observed drying data and the comparative results of the value ofR2; SSE and χ2showed that the cubic polynomial model was much more adequate model for describing the vacuum drying ofZanthoxylumbungeanum. BP neural network was established to compare with cubic polynomial model. The results show that the cubic polynomial model fits withR2of 0.999. The lowest value of SSE is 7E-4; and the lowest value of χ2 is 3.08E-5. It is the best model in describing the dynamic characteristics ofZanthoxylum?bungeanumvacuum drying among seven classical models. However; the average relative error of the cubic polynomial fitting test is 1.98% ; higher than the average relative error 1.13% of BP neural network model. Therefore; BP neural network is the optimal mathematical model to describe the drying dynamics ofZanthoxylum?bungeanum.