Rangelands play a crucial role in Ethiopia's rural economy, ecological biodiversity, and food security. However, their condition at the local level remains inadequately documented, limiting timely responses to degradation. This study aimed to assess rangeland conditions using Normalized Difference Vegetation Index (NDVI) analysis and field data collection methods, employing Landsat 8 Operational Land Imager (OLI) for 2024 NDVI data. In addition to geospatial data, we conducted 123 household surveys, six key informant interviews, and field surveys to evaluate rangeland conditions and identify the drivers of degradation. Our results documented 19 herbaceous species in the study area, with grasses making up the majority (68.5%), followed by two succulent species (10.5%), two forbs (10.5%), and two sedge species (10.5%). We also recorded 24 woody plant species, categorized into 11 trees (45.8%) and 13 shrubs (54.2%). The rangeland condition assessment yielded an average score of 29.4 +/- 6.17 based on seven ecological indicators. NDVI values ranged from -0.02 to 0.41, indicating varying levels of vegetation health, with evidence of both healthy and degraded areas. The findings showed that 1.6% of the land was healthy rangeland, 11.6% was low degraded, 67.8% was moderately degraded, and 19% was highly degraded. The study identified the main drivers of rangeland degradation as the weakening of traditional management systems (93%), population pressure (89%), recurrent droughts (85%), bush encroachment (65%), and agricultural expansion into grazing lands. Key Informant Interviews confirmed statistically significant differences among these drivers (Friedman test: chi(2)(4) = 21.63, p < 0.001), with the weakening of traditional rangeland management ranked highest. In conclusion, this study underscores the urgent need for localized monitoring and management strategies to combat rangeland degradation in the study area. We recommended that policymakers invest in developing and implementing sustainable rangeland management practices that consider traditional knowledge and address the identified drivers of degradation.