Product traceability provides important information for reinforcing hops quality and safety. In this study, multi-metal fingerprinting was used to establish an identification model for classifying hops' geographical origins and varieties. Twenty-two metals derived from hops were analyzed, which were grouped into major, minor, and trace elements. Analysis of variance showed the preliminary relationships between the metals and samples. Hierarchical cluster analysis revealed essential differences among the different hops samples. Principal component analysis reduced 22 variables to two principal components, which identified the varieties and geographical origins of hops. Pearson correlation analysis was used to study the relationships between metals and functional ingredients. Furthermore, hops samples collected from non-main production area were used to verify the experimental model. Our approach can be used for effectively and accurately distinguishing hops based on variety and the geographical origin.