•MS-based untargeted metabolomics was firstly proposed to identify origins of Chinese wines.•There was strong correlation between geographical origins and metabolic profiles of wines.•The differential metabolites were screened as markers by OPLS-DA with pairwise modeling.•Tentative identification of differential metabolites was conducted based on MS and MS2 data.•Reliable OPLS-DA models based on markers were constructed for predicting origins of wines. Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.