Population balance modeling of copolymerization reactions relies on simultaneously integrating the set of coupled ordinary differential equations (ODEs) describing the concentrations of each species in a system. Such methods have been associated with a problem of needing to account for every possible comonomer sequence in a polymer chain, as the active species 'revealed' by a depropagation reaction, as well as the identity of this 'new' chain end's penultimate unit, was believed to be required to accurately account for reaction rates, even when using a terminal model. Thus, the number of equations to solve would scale as 2 n where n is the maximum degree of polymerization; such an approach becomes infeasible even for modest values of n. This drawback has prompted the use of simplifications, e.g., limiting the maximum degree of polymerization to relatively low values or treating only a single monomer type as reversible, to characterize or model equilibrium copolymerization reactions. We note, however, that this dilemma only manifests in the case where both comonomers can undergo equilibrium polymerization. When a single equilibrium comonomer is used, the number of differential equations describing the propagating polymer chain species required to accurately characterize comonomer consumption has an upper limit equal to n + 1. Once a chain propagates an irreversible comonomer, all sequence information preceding that unit in the chain has no influence on any subsequent (de)propagation reactions and thus tracking it is not required. While methods exist to further reduce the number of equations required, as demonstrated by Hutchinson and Penlidis, these methods rely on implementing an analogous assumption as that of Lowry, Izu, Witter, and Kruger in their copolymer equation derivations (vide infra).