Abstract: Support vector machines(SVM) based on structural risk minimization（SRM）is used to model batch fermentation process by considering the complexity and the problem of severe non-linearity in fermentation process.The model based on SVM was featured by less complexity and better prediction ability than that based on artificial neural networks(ANN).The hybrid support vector machines(HSVM) model was proposed by combing SVM with fermentation kinetics mechanism in serial and serial-parallel approaches and used to predict the state of biomass in fermentation.The mechanism analysis and the simulation results showed higher prediction accuracy, more powerful generalization ability and better performance of these two kinds of HSVM in modeling than those based on black-box SVM, simple and approximate kinetics model and the corresponding hybrid ANN.