Learning trajectories vary amazingly widely across countries, regions, and individual students in dynamic ways. In this paper we develop a parametrized structural model of the dynamics of the learning process and use the model for suggestive policy applications. We first synthesize the existing empirical literature on learning profiles, which suggest a clear set of parameters that formally characterize the learning process. We then calibrate this model of the learning process to reproduce the distribution of observed learning outcomes in low- and middle-income countries. Applying our calibrated model to policy simulations, we find that expanding schooling to universal attainment of basic education without changing the dynamics of the learning process would produce very little additional learning. Adjusting other parameters in the model, however, has large, positive effects. Slowing the pace of curriculum, so that more children can keep up, increases average learning in grade 10 by the learning equivalent of 1.6 years of schooling. Expanding the student skill levels that learn from a given level of instruction to account for within classroom heterogeneity of learning levels increases average grade 10 learning by the equivalent of a full year of schooling. The parameters we use are flexible, to accommodate the learning process in different contexts, and future work could explore additional parameterizations and calibrations for informing plans to improve education systems’ coherence for learning.