Tropical rainforests (TRFs) play an important role in regulating the global climate and conserving biodiversity. Leaf area index (LAI) determines the capacity of TRFs for radiation interception and carbon sequestration via photosynthesis while also influencing the water loss from TRF canopies via transpiration. Elevational gradients in tropical environments provide an approach to investigate the influence of environmental variations on key vegetation properties such as the LAI. In this work we determined the concurrent, interactive influences of the elevational gradients of the environment (i.e. selected climatic and soil properties) and vegetation (tree diversity and structure) in determining the variation of LAI of one-hectare permanent sampling plots (PSPs) within TRFs across a wide elevational gradient (from 117 m to 2132 m above sea level). Eight rounds of canopy hemispherical photography were carried out at three-month intervals over a 24-month period from 2019 to 2022. Canopy LAI was estimated using HemiView image processing software. Long-term mean climatic data from 1990 to 2021 were extracted for the PSPs from monthly global weather database of CRU-TS-4.06-bias corrected with WorldClim-2.1. Key soil properties were measured at 0–15 cm and 15–30 cm depths via soil sampling. Tree diversity was determined by a complete census of all trees with equal or greater than 10 cm in diameter at breast height. Total tree biomass was estimated using allometric equations. Linear mixed model analysis of LAI showed significant (p < 0.05) variance for the random effects of elevation and elevation × time interaction. In a majority of measurement rounds, variance of LAI due to elevation was significant while at a majority of elevations, the fixed effect of measurement round on LAI was significant. Leaf area index showed significant linear reductions with elevation in all rounds, at rates ranging from 0.175 to 0.357 per 1000 m. Linear and multiple regression analyses identified increasing maximum cumulative soil water deficit, CSWDMax (an index of water deficit computed as the difference between evapotranspiration and precipitation), as the major climatic factor responsible for the reduction of LAI with elevation. Decreasing solar irradiance (SR) and increasing day-night temperature difference (DTR) with elevation also contributed to the observed LAI trend. Multiple regression analysis showed soil exchangeable potassium (KEx) and available phosphorus (PAv) influencing LAI positively while electrical conductivity (EC) and total nitrogen (NTot) influencing LAI negatively. Variation of Shannon-Wiener tree diversity index (H) and total tree biomass per hectare (TBM) contributed positively to the observed elevational variation of LAI. Factor analysis extracted two underlying factor constructs which accounted for 86 % of the combined variation in climate, soil and vegetation across the elevational gradient. Plot-wise scores of Factor 1, which had CSWDMax, SR, DTR, soil EC, NTot and H loading strongly and accounting for 70 % of the variation, showed a significant linear relationship with LAI. A cluster analysis incorporating the elevational variation of LAI, climate, soil and vegetation clearly classified the TRFs into four ranges of elevation at a linkage distance of 0.75. We conclude that LAI of TRFs in our study decreases with increasing elevation and identify increasing water deficits with elevation as the major climatic factor controlling this reduction.