Leaf area index (LAI) is a key vegetation structural parameter widely used to quantify vegetation dynamics. A thorough understanding of its spatiotemporal characteristics and driving mechanisms is essential for sustainable ecosystem management. This study combines LAI and climate remote sensing data with socioeconomic statistics, and uses the Geographically and Temporally Weighted Regression (GTWR) model and geographic detector to identify the key drivers of LAI changes and their spatial differentiation characteristics. The results indicate a significant upward trend in the LAI across the basin, with a markedly higher growth rate after 2000 (0.0123/year) compared to the period before 2000 (0.0028/year). Spatially, before 2000, 57% of the regions showed an increasing trend in LAI, while after 2000, 69% of the regions exhibited an increasing trend in LAI. In terms of temporal LAI dynamics, in the eastern region, the positive promotion effect of the Grain for Green policy (GRGR) was the most significant factor affecting LAI changes. In the central region, the employed population ratio (EPR) emerged as the dominant factor driving LAI increase. In the western region, the negative effect of the urban-rural income ratio (IR) served as the primary driver of LAI change. Regarding the spatial distribution of LAI, both natural and policy factors were statistically significant. Mean precipitation (MP) and mean slope (MS) exerted the most pronounced influences, followed by mean temperature (MT) and GRGR, whereas mean elevation (MD) showed the weakest effect. Notably, socioeconomic factors did not demonstrate statistically significant impacts on the spatial distribution of LAI. This study provides a theoretical foundation for understanding the driving mechanisms of LAI dynamics in the Yellow River Basin and offers scientific support for ecological restoration and sustainable management in the region.