The origin(s) of life (OoL), which has puzzled scientists for centuries, remains a major scientific challenge in the 21st century. Understanding the processes relevant to the OoL demands theoretical frameworks that can connect processes across scales, from microscopic dynamics to emergent levels of organization. While experimental studies generate a wealth of data, theoretical and computational approaches provide the structure necessary to interpret and generalize these findings. In Part 1, we examined the most widely used experimental techniques in the field. Here, we focus on the mathematical, physical, and computational techniques used to model phenomena relevant to life’s origin(s). We discuss methods ranging from quantum chemistry and molecular dynamics to chemical reaction networks, autocatalysis, and evolutionary modeling, as well as information-theoretic and phylogenetic approaches that link chemical and biological organization. We further highlight emerging trends such as synthetic biology, omics-based methods, and laboratory automation as novel points of contact for theory-experiment integration. Ultimately, we aim to provide an educational tool that can facilitate more post-disciplinary collaborations in OoL research by helping scientists understand what they can do about the problem of life’s origins, rather than telling them how to think about it.