Abstract: OBJECTIVE To evaluate the adaptability of wavelet neural network time series model through predicting the concentration of aspirin in blood. METHODS Four groups of rabbits were fed with aspirin, and plasma concentration data were obtained in 0.15, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 6.0, 13.0, 22.0 h time points. Then through the software MATLAB, 3 groups of experimental data were trained by network, and the trained network was used to predict the plasma concentration data of the left one group. Its characteristics of the compartment model and pharmacokinetic were determined by combination of pharmacokinetics. RESULTS The simulation results were consistent with the actual data, and the absolute mean error of the network was in the range of 0.3%-5.39%. The pharmacokinetics of aspirin in two compartment model was proved by combination of pharmacokinetic simulation. CONCLUSION Wavelet neural network time series model in predicting the plasma concentration of aspirin are with good fitting capability and excellent predictive ability, at the same time with the combination of pharmacokinetics plays a more positive role in promoting modern clinical pharmacology research.