In this work, a systematic approach based on nonlinear experimental design as ail efficient tool for the validation of kinetic models is proposed which has the objective of computing experimental layouts, setups, and controls in order to optimize the statistical reliability of parameter estimates from the resulting experimental data. Furthermore, because the optimum experimental design is dependent oil the Values of the parameters. a sequential design is proposed. This represents ail interaction between proposed experiments (e.g., inlet temperature and concentration), their evaluation, parameter estimation, and new design information Such as reactor layout, sampling points, and temperature measurement positions. This follows ail iterative procedure until all parameters achieve a prescribed statistical quality. Because of the fact that the overlaying optimization problem contains a highly nonlinear objective function, a hybrid optimization framework is also proposed to overcome the problem of local minima. To show the efficiency of the developed framework, it has been applied to the contact reaction. This reaction is a basic step in the sulfuric acid production and is carried Out in a catalytic fixed-bed reactor called the contact horde.