Although many mechanistic studies of gas-oil cracking on fluid catalytic cracking catalysts have been published, only a small amount of literature has described their application for the modelling of sparse data sets amenable to typical evaluations in catalyst screening studies. The well-known microactivity test is the most common approach to determine the activity and selectivities of fluid catalytic cracking catalysts and to predict their performance in commercial FCC units. For this purpose the yields obtained for different catalysts or different feedstocks have to be compared at constant values such as conversion, coke or gasoline. Generally, the values of interest cannot be obtained experimentally and therefore interpolation techniques have to be applied to gain knowledge on the individual yields. However, the small number of experiments usually performed for such studies and the large number of parameters which have to be estimated, if equations derived from reaction kinetics are used, render the utilisation of appropriate models for yield predictions difficult. In this paper a method is presented which enables the modelling of sparse data sets in kinetic terms. FCC catalysts have been characterised with this new approach and its effectiveness was compared with conventional methods. It is demonstrated that the utilisation of informative graphical representations and the application of reduced kinetic expressions lead to an efficient data analysis.