Process-based crop growth models are popular tools with which to analyze and understand the impact of crop management, genotype-by-environment interactions, or climate change. The ability to predict leaf area development is critical to predict crop growth, particularly under conditions of limited resources. Here, we aimed at deciphering growth coordination rules between wheat (Triticum aestivum) plant organs (i.e. between leaves within a stem, between laminae and sheaths, and between the mainstem and axillary tillers) to model the dynamics of canopy development. We found a unique relationship between laminae area and leaf rank for the mainstem and its tillers, which was robust across a range of sowing dates and plant densities. Robust relationships between laminae and sheath areas also were found, highlighting the tight control of organ growth within and between phytomers. These relationships identified at the phytomer scale were used to develop a simulation model of leaf area dynamics at the canopy level that was integrated in the wheat model SiriusQuality. The model was then evaluated using several independent experiments. The model accurately predicts leaf area dynamics under different scenarios of nitrogen and water limitations. It accounted for 85%, 64%, and 73% of the variability of the surface area of leaf cohorts, total leaf area index, and total green area index, respectively. The process-based model of the dynamics of leaf area described here is a key element to quantify the value of candidate traits for use in plant breeding and to project the impact of climate change on wheat growth.