Abstract: In order to solve the problem that it is subjective for archaeological researchers to classify 2D Levallois core by eyes, which cannot produce standard and consistent classification result, the LCAC2D (2D Levallois Core Automatic Classification) algorithm is proposed, which can automatically classify 2D Levallois core. The difficulty of computer core classification is how to convert the Levallois typology classification theory into an algorithm program that can extract distinguishable features of core and automatically classify them. The LCAC2D algorithm used the topological structure of core flute surface to build a weighted directed graph description model, and further optimized the model. The Levallois core was automatically or semi-automatically classified. It was tested on 66 samples, and an accuracy of 77% was obtained. The results show that the LCAC2D algorithm is the first to achieve quantitative analysis of 2D Levallois core.