Advanced model-based experiment design techniques are a reliable tool for the rapid development and refining of process models. Through a practical case study of current interest (a biodiesel production process), we demonstrate the validity of this approach as applied to the planning of optimal experiments for complex kinetics elucidation. The need for an appropriate use of these tools, in particular a judicious problem formulation, is highlighted. A trade-off is found between the predicted precision of the estimates and important experimental aspects (for example, times and costs of the analytical work). The intelligent application of these techniques allows finding experiments which are suitable for the collection of data for complex kinetic networks. A methodology capable of dealing with experiment design problems which involve complex reaction mechanisms is also presented, and advantages and limitations of this procedure are discussed in the light of the results obtained from the parameter estimation.