Objective: To establish a sensitive and specific HPLC-fingerprint method for the quality control of Trionycis Carapax from different areas. Method: The samples from different areas were determined with the method. Mean chromatogram was generated as the representative standard fingerprint and the similarity of each chromatogram against the mean chromatogram was also calculated using the 'Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine' (Version 2004A). Samples were clustered using Hierarchical cluster analysis (HCA) and principal component analysis (PCA) based on the ratio of characteristic peaks and standard peak. Result: Seven common peaks in the HPLC-fingerprint of Trionycis Carapax were obtained

and one peak was identified. In addition

all the similarities were over 0.9.12 batches of Trionycis Carapax from different areas were classified into two groups based on hierarchical cluster

which showed the quality of Trionycis Carapax from different areas was in good consistency. The classification result according to PCA was consistent with the HCA. The PCA showed that seven common peaks were integrated into three principal components (PC) and their accumulation contributing rate amounted to 83.21%. Conclusion: SPSS 19.0 software can be used to cluster samples. Its operation is simple and convenient. The result of statistics is reliable and able to provide a reference for the chemometrics classification and quality evaluation of Trionycis Carapax.