The Tibetan Plateau, often referred to as “the third pole of the world”, is located in the Southwest of China, and makes significant contribution to ecology and climate change in China and around the word. Our study evaluated the change in aboveground biomass (AGB) on the Tibetan Plateau from 2000 to 2020. We used multiple machine learning methods combined with MCD43A4 product data to simulate the aboveground biomass and analyzed the temporal and spatial characteristics of AGB in this region. The main results were as follows: 1) Among the constructed machine learning models, Rborist model demonstrated the highest accuracy, with an R2 of 0.6484 based on screened variables, and eight variables were found to be highly correlated with biomass: precipitation in May, precipitation in June, average temperature in December, normalized difference phenology index (NDPI), precipitation in April, maximum temperature in January, precipitation in August and precipitation in December; 2) AGB in the southeast of the Tibetan Plateau was higher than that in the northwest, with a decreasing trend from the southeast to northwest; 3) AGB on the Tibetan Plateau increased steadily from 2000 to 2020, with an overall positive movement. However, 61.38% of Tibetan Plateau grasslands showed a trend of unsustainability, 4.67% showed a slight deterioration trend, 1.19% showed a significant deterioration trend, and 32.76% were stable or showed a recovery trend.