The utilization of fast-growing exotic species within degraded tropical landscapes presents a significant opportunity to restore ecosystem services whilst sustaining productive land uses. Gmelina arborea, which has been extensively cultivated in Central America, emerges as a promising candidate for sustainable plantation forestry, contingent upon management practices that prioritize resource efficiency and climate resilience. In this research, we undertook the calibration of the 3-PG (Physiological Principles Predicting Growth) model utilizing multi-site field data from northern Costa Rica to simulate growth, canopy dynamics, and water use patterns under a variety of climatic and edaphic conditions. The model demonstrated a high degree of accuracy, with prediction errors remaining below 5% for diameter and above-ground biomass distribution, and under 10% for leaf area index (LAI) and total stem volume. These findings reveal a propensity towards slight underestimation, albeit within acceptable margins for operational application. Additionally, the model exhibits considerable potential for genotype-level calibration, facilitating its deployment in selecting drought-resilient planting material and designing silvicultural practices that mitigate mortality risks under water-scarce conditions while enhancing the efficiency of water and nutrient utilization. In summation, the 3-PG model constitutes a valuable instrument for assessing species adaptability under prospective climate scenarios and optimizing plantation management or genetic selection in regions susceptible to drought. Its integration into landscape planning enhances the efficient allocation of natural resources, contributes to carbon sequestration, and advocates for restoration strategies that eschew competition with natural ecosystems.