The western U.S. has millions of acres of forestlands at risk of large and uncharacteristically severe wildfire. This is due to a variety of factors, including decades of fire suppression as well as climate change. Fuel treatments such as mechanical thinnings, prescribed burns, and combinations of thinning and burning in fire-adapted forests can reduce wildfire severity and potentially stabilize sequestered forest carbon in coniferous, fire adapted forests of the western US; resulting in avoided wildfire emissions (AWE) of greenhouse gases (GHG). Accounting for GHG emission benefits of fuel treatments is challenging; hence, scientific consensus and broad stakeholder buy-in from public agencies, non-governmental organizations, and the private sector is key. Using most recent forest vegetation and weather datasets as well as forest growth and wildfire behavior models, we present an avoided wildfire GHG emission accounting framework developed in collaboration with key stakeholders in the western US as well as recent case studies. This probability-based GHG emission accounting framework can not only provide tools to quantify GHG benefits of fuel treatments, but can specifically be employed to help fund fuel treatments through carbon offset credits. The probability-based nature of this GHG emission accounting approach has further application value for risk accounting to forest carbon stocks from other stochastic events (e.g. drought, insect outbreaks) as well as forest-based carbon offset protocols in general.