This review focuses on kinetic models of depolymerization, which is defined here as thermal, catalytic or solvolytic degradation of polymers to form monomers, oligomers, or otherwise “small” molecules to be used as chemical feedstock or reactant. We split the kinetic models into 4 general categories: machine learning models, continuum models which do not track polymer detail, models which explicitly track the polymer chain length distribution (CLD) or its moments, and kinetic Monte Carlo models. Indicative statistics of the model types and analytical techniques employed in literature are reported. Experimental methods to gather data for building kinetic models are reviewed, including analytical techniques, reactor design considerations, and methods for identifying contaminants. Finally, some challenges facing the field are discussed.