Livestock production in Kenya is a significant source of greenhouse gas emissions, particularly methane (CH4) from enteric fermentation. The objective of the study was to estimate enteric methane (CH4) emission factors (EFs, kg CH4/head/year) for rangeland cattle in Kenya. The study utilized the Intergovernmental Panel on Climate Change (IPCC) Tier 2 method, incorporating animal characteristics, performance data, and diet digestibility. Data were obtained from 1,486 cattle across three locations in Kenya’s pastoral areas: Kapiti Research Station and Wildlife Conservancy (815 cattle), Olkirimatian Community Ranch (347 cattle), and Shompole Community Ranch (324 cattle) all located in southern Kenya. Animal activity data were collected for four seasons during 1 year at Kapiti, and one dry and one wet season in Olkirimatian and Shompole. The EFs were estimated for wet and dry seasons, allowing the calculation of mean annual EFs. The EFs were calculated for the different cattle categories: adult females and males (≥3 years), young males and females (1–3 years) and calves (<1 year). The results revealed significant differences in herd composition, live weight (LW), weight gains, milk yield, and digestible energy (DE) of pasture among the locations, all of which influence CH4 emissions. LW varied among the three locations due to differences in breed between sites and varied substantially compared to Tier 1 assumptions, and DE differed significantly across sites (54.5%–66.4%), despite the Tier 1 approach assuming a fixed DE value for pasture (58%). There was a significant difference (p < 0.05) in the herd level EF of all cattle categories: Kapiti (64 ± 0.9 kg CH4/head/year), followed by Olkirimatian (52 ± 1.2 kg CH4/head/year) and Shompole (42 ± 1.0 kg CH4/head/year). A comparison of the estimated herd level Tier 2 EFs with computed herd level Tier 1 values revealed that Kapiti exhibited 18% higher mean Tier 2 EFs, while it was lower by 7% and 28% in Olkirimatian and Shompole, respectively. These findings highlight the need for system-specific national EFs that better capture the diversity of production systems and breed differences. Policymakers and researchers should revise IPCC default values to incorporate breed-specific factors within systems.