Understanding the multi-scale regulation of methane oxidation potential (MOP) across diverse grassland biomes is critical for predicting climate feedbacks, yet a synthetic framework across large environmental gradients remains lacking. We combined amplicon sequencing with partial least squares path modeling to assess methane oxidation potential (MOP). Our study spanned three Northern Hemisphere grasslands: Inner Mongolia, the Loess Plateau, and the Qinghai-Tibetan Plateau. Each region included three distinct ecosystem types. The results reveal that the dominant drivers of methane oxidation differed across the three grassland regions studied. At the regional scale, climatic factors were predominant with the aridity index (AI) and mean annual temperature (MAT) accounting for more than 50% of the variation in MOP through cascading associations with soil properties, plants, and methanotrophic community structure. These patterns were linked to variations in key soil properties (such as silt content), plant attributes, and methanotrophic community composition. At the sub-regional scale, the primary controlling factors diverged: MOP on the Qinghai-Tibet plateau was best predicted by AI, consistent with a mechanism of gas diffusion limitation; on the Loess Plateau, MAT was the key limiting factor, primarily influencing methanotrophic community composition and enzyme kinetics; in the nitrogen-limited grasslands of Inner Mongolia, NH4+-N availability was the major constraint, governed by the balance between nutrient competition and supply. Ecosystem-specific patterns further refined MOP predictions: in meadow steppes, MOP was positively associated with both the upland soil cluster gamma (USC gamma) abundance and MAT; in typical steppes, plant species composition was key predictor; whereas in desert steppes, showed mean annual precipitation (MAP)-dependent suppression of MOP (negative correlation with MAP), which was counteracted by AI-enhanced gas diffusion. This multi-scale analysis highlights how climate-plant-soil-microbe interactions regulate CH4 uptake. Incorporating these mechanisms into Earth System models will help reduce uncertainties in predicting the grassland methane sink under future climate scenarios.