The research into and applications of wood origin traceability technology are of great significance for promoting the standardization and legality of the global timber trade. This paper focuses on analyzing the content of ten mineral elements and the ratios of stable isotopes δ¹³C and δ¹⁵N in ash samples. Furthermore, multivariate statistical analysis was conducted to assess the clusters and differences in mineral elements, as well as δ¹³C and δ¹⁵N, among the samples, for identifying the different factors used to trace the origin of ash imported from different regions. Through unsupervised clustering and supervised discriminant modeling, a highly accurate method for discriminant analysis was developed. The results reveal significant differences (p < 0.05) in the contents of Mg, Cu, and Sr, as well as δ¹⁵N, between European and American samples. Additionally, the normalized results of mineral elements and isotope ratios were then subjected to partial least squares–discriminant analysis (PLS-DA), resulting in the highest level of separation. This analysis achieved an overall accuracy of 96.2% in discriminating between samples of European and American ash. The chemometrics analysis method integrating stable isotope analysis with elemental analysis exhibited potential for discriminating between samples from European and American ash.