The serpentine microchannel or bent microchannel has been identified as one of the essential elements for inertial microfluidic devices. Understanding the transient flow of liquid is important in predicting flow time and evaluating device performance. In this paper, based on the unsteady Bernoulli equation, the inertial transient flow model was derived by analyzing the microchannel resistance factor using back propagation (BP) artificial neural network (ANN). In order to train the ANN, an improved BP algorithm was used to make the resistance model more accurate. A centrifugal test platform was employed to measure flow time in the microchannel with different structure sizes. The results show that the transient flow model has a good agreement with the experiment values, the results also show that the method using BP neural network can also be used to solve the problem of nonlinear inertial flow.