Despite the increasing use of the microgenetic methodology to examine change, the techniques employed to analyse microgenetic data remain fairly unsophisticated. This paper reviews the existing ways of analysing such data and describes their limitations.We use two recent studies to illustrate how modelling can avoid these problems and reveal important aspects of children’s cognitive development. The first example illustrates the use of quasi-binomial modelling to examine 6- and 7-year olds’ analogical reasoning development. This method offered insights into the way in which children develop, in terms of the rate and path of change, and how different instructional cues can affect their performance. The second study employs a random effects logistic model to analyse the development of preschoolers’ counting skills. This technique was employed to examine different influences on children’s use of counting to compare quantities. We argue that the key benefit of such modelling approaches is that they are able to tap into the process of change whilst not compromising statistical assumptions.