The aim of the present study was to analyze a method for identifying the aging time of raw Pu-erh tea. Based on the contents of multiple quality components of 21 tea samples aged for 1~32 years, functional models with a high degree of correlation were established. The developed models were subsequently applied to the identification and verification of aging time in 23 samples from different sources. According to the results, eight indicator components, namely, color difference values (L*, a*, and b*), theabrownin, gallic acid, caffeine, ester-type catechin, and total catechin contents, of raw Pu-erh tea infusions were strongly correlated with aging time. All correlation coefficients of the univariate quadratic regression equations exceeded 0.9, whereas those of the linear equations exceeded 0.8. Therefore, the aging time of unknown samples could be calculated based on the indicator contents. Sample verification revealed that, for samples aged less than 24 years, the average value calculated using two equations for eight indicators provided a better estimate. Among 13 samples, the calculated aging time of 11 samples differed from the actual value by 0.1~3.4 years, whereas that of the remaining two samples differed by 5.3~6 years. For samples aged 28~100 years, the linear equations based on four indicator components, namely, L*, a*, b*, and theabrownin content, provided better estimates, with the calculated aging time of six out of 10 samples being relatively close to the actual storage duration (years). In conclusion, functional models were established by exploring the correlations between the contents of multiple quality components and aging time of raw Pu-erh tea. These models could serve as a convenient, feasible, and practical new method for identifying the aging time of raw Pu-erh tea.