‘Living’ radical polymerization has opened the way to producing complex polymer architectures, including cyclic polymers, dendrimers, stars and many other structures. A major issue in the field of polymer science is the characterization of these polymer products, especially when made to high molecular weights, well beyond the accuracy of NMR or MALDI. Questions of purity arise due to the amount of side products (e.g. dead polymer through termination or cyclic purity). Here, we use the log-normal distribution model to fit distributions of all products to the overall experimental distribution. The fits in all cases were excellent. The log-normal distribution model was simple to implement as it only relies on a two-parameter fit, in which these two parameters, the standard deviation and median, were obtained from the number-average molecular weight and the polydispersity of the molecular weight distribution. This type of analysis can play a role in elucidating the side product distributions, leading to new or modified mechanistic insights.