The lithology of the transitional facies strata between sea and land in the eastern margin of the Ordos Basin is complex, and the rock mechanics parameters and rock physics response are complex, resulting in insufficient prediction accuracy of rock mechanics parameter prediction models based on traditional methods.The rock mechanics test and the matching acoustic wave and density test were adopt, the parameters of rock sample density, acoustic wave velocity, strength and elastic in the study area were gained, and then carry out the prediction research of rock mechanics parameters based on traditional methods. On this basis, multiple algorithms are selected to build different types of rock mechanics parameter prediction models; According to the prediction effect of different algorithm models, an intelligent fusion prediction model is constructed; The research results show that the traditional methods cannot accurately predict the rock mechanics parameters of the marine continental transitional facies strata in the eastern margin of the Ordos Basin. Different machine learning algorithms have different prediction effects on different types of rock mechanics parameters, and the average relative error is more than 20%, that is, a single machine learning algorithm model is difficult to achieve synchronous and accurate prediction of different types of rock mechanics parameters; The intelligent fusion model has a high prediction accuracy for different types of rock mechanics parameters. The average relative errors of the test set and the training set are about 8.14% and 13.02%, respectively, indicating that the model has achieved synchronous and accurate prediction of different types of rock mechanics parameters; This model is applied to the calculation of horizontal principal stress in the research area, and the relative error between the predicted value and the measured value is relatively small, reflecting that the model can be applied to improve the accuracy of the calculation of horizontal principal stress in the formation.