 Grassland fires are a major threat to the environment, human life, and economic development. To address this issue, researchers have been looking for ways to accurately predict the probability of grassland fire occurrence. This study focused on Inner Mongolia, where limited research has been done on grassland fire prediction. By using remote sensing data and other environmental variables, multiple regression models were developed to identify the drivers of grassland fire occurrence and predict its probability. The results showed that meteorological factors and a certain type of vegetation index were important indicators of grassland fire occurrence. Additionally, the study found that different areas respond differently to these drivers, with some having longer fire prevention periods than others. Therefore, a grassland fire management strategy based on local conditions should be adopted, and existing fire monitoring systems should be improved by incorporating remote sensing data of grassland fuels to increase accuracy. This article was authored by Chong Chong, Yu Chong, Ziping Xiong, and others. We are article.tv, links in the description below.