<p>Accurate prediction of the tool wear state is conducive to improving the dimensional accuracy and surface quality in micro milling. However, there are various ways to characterize the tool wear, and the tool wear in different dimensions (e.g. flank wear of one-dimensional and wear area of two-dimensional) is difficult to be described by a unified wear model. Furthermore, the runout not only has a significant impact on tool wear, but also causes asymmetrical wear of tool teeth. As for these problems, this work proposes and develops a general tool wear prediction model including machining parameters, cutting force, cutting length and runout, which can be applicable to both 1D length and 2D area wear prediction. First, an empirical model that considers the effect of cutting force is established. Then, an improved model for prediction of wear length and wear area is developed. Finally, the runout factor is introduced to reflect the asymmetry of the wear of cutting teeth in micro milling. By comparing the experimental results with the theoretical prediction results, the accuracy and effectiveness of the proposed model are proved. In addition, the influence of runout on the asymmetry of cutting tooth wear is discussed. The research results of this work are conducive to achieving online monitoring of tool wear in micro milling.</p>