Vegetation resilience is vital for maintaining ecosystem stability and preventing land degradation, particularly in arid regions like Central Asia that are increasingly affected by frequent and intense droughts. Understanding vegetation recovery processes and their key drivers is essential for assessing ecosystem responses in the postdrought context. This study employs the Standardized Precipitation Evapotranspiration Index (SPEI), along with Normalized Difference Vegetation Index (NDVI) and Gross Primary Productivity (GPP) datasets, to investigate post-drought vegetation recovery in Central Asia. Drought characteristics were identified using run theory. Based on a resilience framework, we quantified vegetation greenness and productivity in terms of resilience and recovery time, and assessed the relative contributions of key drivers to changes in vegetation resilience. Results show that in northern Kazakhstan, up to 11 drought events occurred, whereas the Aral Sea region and Xinjiang experienced fewer but more intense and prolonged droughts. Vegetation greenness exhibited strong negative anomalies (minimum: 4.1), with faster recovery observed in wetter regions such as northeastern Kazakhstan and the Tianshan Mountains. Vegetation productivity demonstrated higher resilience and shorter recovery times than greenness. Attribution analysis revealed that vegetation greenness resilience was mainly driven by temperature (31.68 %) and solar radiation (28.08 %), while precipitation and vapour pressure deficit jointly explained 70.6 % of the resilience in productivity. Compared to previous studies, our findings highlight the importance of understanding both vegetation recovery processes and the spatial dynamics of their climatic drivers. These insights conservation strategies in Central Asia, with implications for enhancing ecological resilience and advancing sustainable development goals.