Our modeling outlined below is structured into three key sections to enhance the predictive power of our bioengineering approach. First, “Inside Cow” investigates the impact of our solution on the metabolites involved in methane production and the complicated rumen microbiome. Second, “Outside cow” uses regression algorithms and machine learning to analyze how variations in cattle feed composition influence methane emissions, aiming to identify microbial biomarkers for targeted methane reduction. Lastly in “Algae n Enzymes,” we model the breakdown of Chlorella vulgaris cell walls from the release of the lytic enzyme PeiR, employing thermodynamic modeling and Monte Carlo simulations. Our modelling approaches attempts to make our bioengineered solution more predictive, and answers key questions that cannot be explained solely by literature reviews and laboratory results.