Corrosion of reinforcing steel in concrete structures can significantly compromise their performance. Accurately estimating this deterioration for in-service structures is challenging due to uncertainties surrounding the distribution of internal corrosion and cracking patterns, compounded by the limitations of destructive testing. This research proposes a novel approach to predict the remaining load-bearing capacity of corroded reinforced concrete (RC) structures based on the pattern of surface cracks caused by corrosion. The method integrates a model predictive control (MPC) algorithm with a three-dimensional Rigid Body Spring Model (3D RBSM) to estimate internal corrosion levels from observed cracks and a normal 3D RBSM simulation to predict the residual performance. The proposed system is validated through analysis of four corroded beam specimens based on experimental work reported in the literature. In use, the MPC algorithm first estimates a corrosion distribution in a RC beam and generates simultaneous corrosion-induced crack and stress predictions. This information is then used to predict residual load-bearing capacity. The system accurately forecasts the non-uniform corrosion distribution, flexural capacity, and load-displacement curves of a specimen, offering insight into the performance differences among the specimens and demonstrating its potential to assess the serviceability of existing RC structures with corrosion issues.