We describe a new rationale to kinetic modelling in which adjustable parameters are avoided through the use of quantum chemistry. This new approach reverses the standard modelling approach in which, having first assumed a kinetic model, it is then fitted to the experimentally determined values of the macroscopic properties (rates, compositions, molecular weight distributions, and so forth) so as to estimate the rate coefficients of the individual reactions. Instead, one still assumes a reaction scheme, but then calculates the rates of the individual reactions using high-level ab initio calculations, and in this way a kinetic model is built that can be used to predict the macroscopic properties of the process from first principles. These can then be compared directly with experiment (for benchmarking purposes) and subsequently be employed to predict the outcome of new chemical processes. In here we illustrate the ab initio modelling technique, using a recent study of initialization in RAFT polymerization as a case study. We also discuss its advantages and possible problems, and highlight some of its potential applications in the radical polymer field.