Mangrove forests’ restoration has gained traction as a sustainable solution to mitigate the effects of greenhouse gas emissions and to provide ecosystem services, such as coastal protection. Restoration projects are often informed by expert judgment rather than a quantitative understanding and have a high failure rate. Monitoring mangrove restoration performance may take decades and has a strong case study dependency. To optimise restoration strategies, we developed an individual-based mangrove and process-based hydro-morphodynamic model to simulate multi-species mangrove forest trajectories, including the physical environment’s feedback. We find a significant impact of planting zonation on the mudflat behaviour, with seaward erosion and in-forest-landward deposition. Planting mangroves close to mean sea level decreases carbon storage potential due to increased mudflat erosion. Configuring planting in multiple patches proves beneficial to mangrove biomass development, expansion, and sediment accumulation. Combined with sound monitoring, the developed tool can potentially optimize planned mangrove restoration strategies.