Abstract: Geographic traceability technology for aquatic products serves as a crucial tool for supporting the implementation of the “Ten-Year Fishing Ban” policy in the Yangtze River. To enhance the enforcement capabilities of regulatory authorities, this study utilized crucian carp (Carassius auratus) as the subject. Based on regional differences in muscle fatty acid profiles, chemometric techniques including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA) were employed to construct geographic origin discrimination models. The model distinguishing Yangtze River and non-Yangtze River samples achieved an overall classification accuracy of 96.4%, with a cross-validation accuracy of 94.0%. The model further developed for distinguishing samples from different sections of the Yangtze River demonstrated even higher performance, reaching 100% total classification accuracy and 96.7% cross-validation accuracy. These findings indicate that fatty acid profiling combined with multivariate statistical analysis provides an effective approach for geographic origin identification of crucian carp. This method holds strong practical applicability and potential for wider adoption, offering valuable technical support for the implementation of the fishing ban policy, aquatic product market supervision, and ecological conservation in the Yangtze River basin.