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Reliable origin authentication methods are critical for protecting high-value food products with designated geographical origins. A total of 623 tea samples were collected from important green tea production regions around China from 2012 to 2016. A Random Forest model (RF) with 19 input predictors (e.g., δ¹³C, ²⁴Mg, ⁸⁵Rb, and ²⁰⁶Pb/²⁰⁷Pb) was developed. Our RF model not only discriminated Westlake Xihu Longjing green tea (XHLJ) from other regions with an accuracy of 97.6%, but also correctly identified green tea from surrounding regions with an accuracy of 97.9%. The geographical discrimination of tea subsequently harvested in the following years also showed good reliability. Predictive accuracies were higher than 91%. ⁸⁵Rb, ²⁴Mg, δ¹³C and ³⁹K were the most important geographical proxies for determining geographical origin of tea with a relative contribution of 20.6%, 12.5%, 12.1% and 7.4 …