Self-excited vibrations of the face milling process can result in instability, poor surface finish and machine tool failure. In order to avoid chatter vibrations, this article develops an algorithm for predicting the stability lobes for face milling processes. It considers the factors including radial instantaneous chip thickness, entry and exit angles and the dynamic interaction between cutting tool and workpiece which is often neglected by many researchers. An electronic impact hammer is used to identify the dynamic parameters of the face milling system. Milling experiments have been conducted to validate the predictive capability of the developed algorithm for stability lobes. The results show that the prediction model can estimate the stable and unstable zones for face milling process. This article provides a frequency-domain method for establishing stability lobes which can predict stability zones rapidly. The outcome of this research will bring about methodologies for cost-effective monitoring of face milling processes and maximize the material removal rate.