Driven by the global competition and market demand, the petroleum industry is under increasing pressure to produce clean, high-value products from low-cost feedstocks with minimum capital outlays. This has triggered an urgent need to develop robust process models capable of predicting the effects of feedstock composition, operating conditions, and catalyst properties on product quality. To develop such models, one generally splits the reaction mixture at the molecular level, examines microscopic interactions among individual reactions, and then works all the way up to the macroscopic level. Along the way one performs lumping to keep the size and complexity of the problem at bay. This is not only crucial for practical applications, but also important for fundamental understanding, since one does not want to lose sight of the forest for too many trees. This paper gives an overview of new and emerging theoretical tools for building kinetic models for hydrocarbon processing. While the emphasis is on reaction kinetics, the question of reducing hydrodynamic complexities is addressed as well.