Functional acrylic resins for the coatings and adhesives industry are often synthesized by radical solution copolymerization at high temperatures (>120 degrees C) using starved-feed semibatch operation. The kinetic Monte Carlo (KMC) stochastic modeling technique has emerged as a method to represent the placement of the functional comonomer units across the polymer distribution, thus providing the knowledge required to increase process efficiency and product quality. However, obtaining such information is computationally intensive, limiting the utilization of the method. To avoid this barrier, a series of mathematical expressions based on the Schulz-Flory probability distribution is derived to estimate the instantaneous mole and weight fractions of polymer chains containing a specific discrete number of comonomer units. A comparison of the results to those from a previously established KMC implementation demonstrates that the strategy can reasonably match the distribution of functionality obtained from the KMC simulator. This deterministic approach is then extended to the cumulative measures with satisfactory precision.