Automated mechanism generation is an essential tool to be able to create mechanistic models of lubricant degradation chemistry. To date, modeling of lubricant degradation has been accomplished only through the use of lumped or pathways-style approaches. These methods have yielded important insights into major degradation pathways but lack predictive power and fail to produce some key trends in the product distribution, even qualitatively. Mechanistic models of lubricant degradation include reactivity of individual species as well as the role of secondary reactions. Such models have much to offer in terms of fundamental understanding of degradation chemistry. Furthermore, they may be exploited to directly study the effect of radical stabilizers and additives. Key results obtained include a quantitative description of the degradation of a model lubricant as well as detailed kinetic correlations for estimating rate constants. This poster presents our efforts to construct detailed reaction mechanisms of lubricant degradation. The underlying theories of automated network generation and preliminary results are presented.