<p>The machining error caused by elastic deformation during the machining of thin-walled part can seriously affect the machining quality and performance of the part. Therefore, accurate prediction of machining error caused by elastic deformation is crucial for analyzing and controlling machining error. However, existing prediction methods do not fully consider the influence of the dynamic response of elastic deformation, resulting in significant prediction error. In this study, a prediction model of machining error considering the dynamic response of elastic deformation is proposed, and the accurate prediction of machining error is achieved by iterative calculation and the Gaussian Process Regression (GPR) algorithm. Firstly, based on the iterative calculation of cutting force, chip thickness, and elastic deformation, a prediction model of machining error without considering the dynamic response of elastic deformation is established. Then, the prediction model is modified by introducing the dynamic response modification coefficient (DRMC), which is calculated by the GPR algorithm and can significantly improve the accuracy of the prediction model of machining error. Finally, the accuracy of the prediction model of machining error considering the dynamic response of elastic deformation is verified by experiment. The prediction model can not only accurately predict the machining error of finish milling of thin-walled part, but also effectively reflect the dynamic characteristic of the dynamic response of thin-walled part. The proposed prediction model will provide powerful technical support for analyzing and controlling the machining error of thin-walled part caused by elastic deformation.</p>