Developing non-destructive indicators from leaf-level hyperspectral reflectance is the first step in mapping endangered tree species in the tropic. Therefore, hyperspectral reflectance at the leaf level was implemented to differentiate 15 tree species from Costa Rica's wet forests. Hyperspectral reflectance (310 to 1100 nm) was evaluated in six individuals per species (30 leaves per individual) in rainy season, in addition, specific leaf area (SLA) and leaf thickness (LT) were evaluated. The data were first analyzed with one-way ANOVA to identify differentiating bands between species. Then, linear discriminant analysis (LDA) was used to classify species and define the degree of similarity; the contribution of each narrow band to the classification was estimated with the absolute value of standardized coefficients associated with the discriminant function (kappa value). Subsequently, it was analyzed whether the SLA or LT correlated with species differentiation. The results showed that wavebands al 350, 700, 750, 780, 790, 800 and 1010 nm were key to differentiating the species, with an average kappa value of 0.88. Furthermore, the correlation of hyperspectral reflectance with SLA and LT was ruled out. Our results suggest differentiating tropical tree species with non-destructive methods, which will facilitate mapping endangered populations and the development of conservation strategies.