: Bio-derived fuels are expected to progressively displace conventional fuels in an effort to reduce dependence on crude oil and mitigate environmental impact. Bio-fuels are very diverse, leading to new opportunities to tailor fuel blends to achieve desirable properties, such as low emissions. Beyond fuel formulation, a key step is to understand how fuel molecules with very different chemical functionalities interact during combustion to eventually be able to better control emission formation. As a first step to address these challenges, a novel numerical tracking algorithm is presented that allows tracking of specific atoms during homogeneous combustion as they are transferred from reactants to products throughout a chemical kinetic network. Tracking is performed by labeling individual atoms or groups of atoms of interest that are present in the system initially, and solving appropriate tracking equations providing the concentration of tracked atoms at each possible location on each chemical species involved, in addition to the coupled ordinary differential equations describing the time evolution of species concentrations. The transfer equations for a given chemical kinetic mechanism are automatically generated using a constrained hierarchical pattern matching algorithm, or CHPMA, which relies on simple structural and energy-based arguments to characterize and quantify how, in each elementary reaction, atoms are re-organized as reactants are converted into products. In this work, the overall methodology will be presented, with a focus on the CHPMA algorithm. The capabilities of the tracking algorithm will then be illustrated by analyzing soot precursors formation during fuel-rich combustion, providing new, quantitative evidence of well-known behaviors observed in experiments, such as the link between the molecular structure of a fuel and its sooting propensity.