In a rapidly changing society, complex policy issues across a range of areas affecting children require a coordinated and responsive approach based on the best evidence available. We report on a dynamic microsimulation model that aims to capture the underlying drivers and determinants of progress in the early life course across various domains including health and education. The model resides in a decision-support tool that was developed in partnership with end-users. To build a realistic model we used micro-data from a major New Zealand longitudinal study that follows a birth cohort through the years of childhood. We describe the development of the model: the conceptual framework, the base sample, the statistical underpinnings, and the simulation process. We go on to show examples of how the model can be used to test various scenarios by modifying key factors on putative outcomes. In this way, the impact of potential policy options or interventions can be assessed. We conclude with an assessment of the benefits of our modelling approach and our specific model.