Methane emissions from enteric fermentation in beef cattle are a major source of greenhouse gases in Argentina, contributing notably to the country's total emissions. Quantifying these emissions is challenging and involves considerable uncertainty. This study aimed to quantify the uncertainty in methane emission estimates and to assess the contribution of key input variables to this uncertainty. Methane emissions were estimated following Argentina's national inventory methodology, using a tier 2 approach based on the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Monte Carlo simulations were applied to incorporate uncertainty in inputs, generating 10,000 iterations to estimate emissions and assess their variability at a 95% confidence level. For 2020, mean methane emissions were estimated at 46.6 MtCO 2 e, with a 95% confidence interval of 37.9–54.5 MtCO 2 e, corresponding to an uncertainty of −17%; +19%. Feed digestibility was the largest contributor to emissions uncertainty, accounting for 41%, followed by the methane conversion factor, contributing 19%. When both variables were fixed, the uncertainty decreased to −2%; +3% with a confidence interval of 44.7–47.1 MtCO 2 e. Improving the accuracy of feed digestibility and methane conversion factor estimates is essential to reduce uncertainty and enhance the reliability of national greenhouse gas inventories.