In the individualized treatment of a patient with Coarctation of the Aorta (CoA), a non-severe case which initially exhibits no symptoms, and thus requires no treatment, could potentially become severe over time. This progression can be attributed to insufficient growth at the coarctation site relative to the overall growth of the child. Therefore, an agent-based model (ABM) to predict the aortic growth of a CoA patient is introduced. The multi-scale approach combines Computational Fluid Dynamics (CFD) and ABM to study systems that are influenced by both mechanical stimuli and biochemical responses characteristic of growth. Our focus is on ABM development;​ thus, CFD insights were applied solely to enhance the ABM framework. Comparative medicine was leveraged to develop a species-specific ABM by considering the rat and porcine species commonly used in cardiovascular research together with data from healthy human toddlers. The ABM luminal radius prediction accuracy was observed to be 79% for rat, above 95% for porcine and 91. 6% for the healthy toddler;​ while that observed for the growth rate was 38.7%, 90% and 64.3% respectively. Given its performance, the ABM was adapted to a 2.5-year-old patient-specific CoA. Subsequently, the model predicted that by age 3, the condition would worsen, marked by persistent CoA enhanced by the predicted least growth compared to growth predicted in the rest of the aorta, hypertension, and increased turbulent flow;​ thus, increased vessel injury risk. The findings advise for incorporating vascular remodelling into the ABM to enhance its predictive capability for intervention planning.