Measuring photosynthetic capacity using gas exchange systems such as the LI-COR 6400XT is time-consuming and limited by stomatal dynamics, particularly in large-scale field applications. Spectral reflectance-based tools, such as the PolyPen 400 UV-VIS, offer a rapid and non-destructive alternative. The present study aimed to develop predictive models for estimating photosynthetic parameters from spectral reflectance data, using immature rubber trees (Hevea brasiliensis) grown under nutrient omission treatments. Five treatments Treatment A: NPK (5.29-8.01-5.34 g plants-1 month-1); Treatment B: -K (5.29-8.01-0 g plants-1 month-1); Treatment C: -P (5.29-0-5.34 g plants-1 month-1); Treatment D: -N (0-8.01-5.34 g plants-1 month-1); Treatment E: Control (-NPK 0-0-0 g plants-1) were applied in a completely randomized design with five replications. Photosynthetic parameters—maximum carboxylation rate (Vcm¿¿), maximum electron transport rate (Jm¿¿), and triose phosphate utilization (TPU)—were measured using the LI-COR 6400XT, while spectral reflectance was recorded using the PolyPen 400 UV-VIS during the second and third leaf flushes. Multiple linear regression models were developed and validated using root mean square error (RMSE). Key wavelengths for estimating photosynthetic parameters were identified in the ultraviolet and near-infrared regions: Vcm¿¿ (R324, R329, R334, R349, R379, R384, R394), Jm¿¿ (R339, R785), and TPU (R324, R339, R404, R785). Model accuracies under self-validation were 90% (Vcm¿¿), 55% (Jm¿¿), and 75% (TPU), and under cross-validation were 84%, 47%, and 64%, respectively. These results demonstrated the potential of reflectance-based models as efficient tools for estimating photosynthetic capacity in immature rubber trees, particularly in resource-limited environments.