The Q-e scheme is remarkably useful in interpreting and predicting the reactivity of a monomer in free radical copolymerizations. In the present work, two support vector regression (SVR) models were developed to predict parameters Q and e in the Q-e scheme. Quantum chemical descriptors used to build SVR models were calculated, for the first time, from transition state species with structures (CH3CHR3)-H-1-H-2 center dot or center dot(CH2CH2R3)-H-1-H-2, formed from vinyl monomer (CH2CHR3)-H-1-H-2 + H center dot. The optimal -SVR model of lnQ (C = 130, = 0.2, and = 1.0) based on 70 monomers has the root mean square (rms) error of 0.336 and correlation coefficient (R) of 0.982. The optimal epsilon-SVR model of e (C = 1.2, = 3, and epsilon = 10(-2)) produces rms = 0.259 and R = 0.963. Compared with previous models, the SVM models in this article have better predictive performance. Results of the study suggest that calculating quantum chemical descriptors from the transition state structures to predict parameters Q and e in the Q-e scheme is feasible. This investigation encourages the further application of transition state descriptors to other quantitative structure-activity relationships (QSARs). POLYM. ENG. SCI., 53:2151-2158, 2013. (c) 2013 Society of Plastics Engineers