Abstract: Small mammals play a very important role in late Cenozoic biostratigraphy and biochronology. Especially since screen-washing technology began to be applied in paleontological investigations, it has often been possible to acquire large samples of small mammal fossils, which makes them a more effective proxy for biostratigraphy and biochronology than large mammals. Accordingly, classification and identification of these large samples have become a fundamental paleontological task. However, when dealing with them using empirical or intuitive traditional morphological methods, it is impossible to avoid paying too much attention to some slight and inconsistent differences and “oversplitting” taxonomic units, or conversely neglecting some consistent differences that are imperceptible to human eyes and lumping several taxonomic units together. In either case, subjective factors will introduce a degree of arbitrariness into the classification and identification of the specimens. To avoid this, a quantitative geometric morphometric method of classification and identification based on analysis of large samples is explored in this paper. The subjects of this case study are 1284 isolated molars of Mimomys gansunicus, Heteromimomys zhengi and Villanyia fanchangensis from the lower Lower Pleistocene Renzidong site, and 163 specimens ofMimomys bilikeensis from the Lower Pliocene Bilike site are used as a point of reference. 7-14 2D homologous landmarks were defined on the occlusal surface of each of the six molars and used as the basis for a linear discriminant analysis. The results confirm that there are three different arvicoline species in the Renzidong sample, and the linear discriminant functions produced in the analysis can describe the consistent differences that exist among the species in this large sample. Furthermore, the same functions can be used as a basis for identifying newly recovered fossil specimens of related arvicoline species. Because geometric morphometrics can deal with both discrete landmark data and continuous outline data pertaining to significant morphological characters, and is suitable for use in both 2D and 3D, this method can be generally applied to the classification and identification of small mammal fossils.