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In peripheral milling, surface accuracy is crucial for the quality of the machined components, and it is one of the reasons why milling is still essential in the manufacturing field. Nonetheless, both static phenomena, like tool deflections, and dynamic issues such as forced vibrations, impact on the accuracy of the components causing surface errors. In this context, the prediction of surface error is an important tool to guarantee surface accuracy and increase productivity at the same time. This paper presents a novel approach to predict surface location error in 2.5-axis peripheral milling operations considering the stiffness variation along the axial depth of cut. The proposed approach discretizes the endmill in small discs, and it evaluates analytically the cutting force along the cross-feed direction for each disc in the frequency domain. Then, tool dynamic stiffness, which is expressed in terms of frequency response function (FRF), is computed considering the stiffness variation along the tool axis. Finally, the presented approach couples the cutting forces with the tool stiffness, and it evaluates surface error along the tool axis. The method was experimentally tested in different conditions to verify its effectiveness and its limits. The results obtained show how static and dynamic aspects and stiffness variation contribute to surface errors in peripheral milling operations. [Display omitted] • Surface location error along the axial depth of cut in 2.5-axis milling is accurately predicted. • Analytical formulations for cutting forces in frequency domain are proposed. • A RCSA-based approach to predict tool FRF variation along the axial depth of cut is presented. • The proposed approach considers both forced vibrations and variation of the tool dynamic stiffness. • Accuracy of the method is proven by experimental validation on several milling tests. [ABSTRACT FROM AUTHOR]