Objective To predict the constitutive parameters of the superelastic model of plantar soft tissue based on random forest algorithm and BP neural network algorithm, to improve the efficiency and accuracy of the method for obtaining constitutive parameters.Methods First, a finite element model of the spherical indentation experiment of plantar soft tissue was established, and the spherical indentation experiment process was simulated to obtain a dataset with nonlinear displacement and indentation force relationships.The dataset was divided into a training set and a testing set, and the built random forest (RF) model and BP neural network (BPNN) model were trained separately. The constitutive parameters of plantar soft tissue were predicted through experimental data.Finally, the mean square error (MSE) and the coefficient of determination (R2) were introduced to evaluate the accuracy of the model prediction, and the effectiveness of the model was verified by comparing the experimental curves.Results The combination of RF model and BPNN model with finite element simulation is an effective and accurate method to determine the constitutive parameters of plantar soft tissue superelasticity, after training,the MSE of the RF model reached 1.3702×10-3, and the R2 reached 0.9829;the MSE of the BPNN model reached 4.8581×10-5, and the R2 reached 0.9993.The inverse-determined constitutive parameters of plantar soft tissue suitable for simulation are obtained. The calculated response curves of the two sets of constitutive parameters predicted are in good agreement with the experimental curves.Conclusion The prediction accuracy of the constitutive parameters of plantar soft tissue superelasticity based on artificial intelligence algorithms modelis high, and the relevant research results can also be applied to the study of other mechanical properties of plantar soft tissue. At the same time,this study provides a new method for obtaining constitutive parameters of plantar soft tissue, which helps to quickly diagnose clinical problems such as plantar soft tissue lesions.