Global concerns about the impact of agriculture, particularly regarding methane emissions from enteric fermentation in livestock, highlight the need for more effective strategies to mitigate these emissions. The CarbonSECO platform, designed to generate carbon credits in Brazilian rural areas, emerged in response to the growing importance of carbon credits to offset greenhouse gas (GHG) emissions. However, additional solutions are required to comprehensively address GHG emissions in the agricultural sector. This article extends the CarbonSECO platform, aiming to quantify, monitor, and control carbon emissions from enteric fermentation in livestock. Through ontologies and machine learning techniques, the platform provides solutions to assess and manage the environmental impact of livestock farming. These advancements directly address mitigating carbon emissions in Brazilian dairy farming. A case study involving 25 monitored farms demonstrates the platform’s ability to predict future emissions and milk production, offering decision-making tools for sustainable agricultural management. The results underscore the effectiveness of these services in promoting environmentally sustainable practices in livestock farming.