In face milling processes, the surface roughness of the machined part reflects the cutting performance of face milling cutter. Surface roughness depends on different factors including feed direction, axial and radial run-out errors, and cutting tool geometry. In this paper, an algorithm considering the effects of static and dynamic factors on surface roughness for predicting the surface roughness is proposed. This work is focusing on straight-edged square insert. The dynamic characteristics of the milling process are also introduced. An electronic impact hammer is used to identify the dynamic parameters of the cutting system. Milling experiments are conducted to validate the prediction model. Results show that the prediction model can estimate the surface roughness of the machined parts after face milling. This paper provides an in-depth understanding of the relationship between machined surface roughness and process conditions especially for axial and radial run-out errors induced by static deformation and Z -axial relative displacement induced by forced vibration. The outcome of this research will lead to methodologies for cost-effective monitoring and surface roughness control.