Stress corrosion is a common and complex deterioration type in large steel civil infrastructure such as miter gates. The diagnostics and prognostics of corrosion damage in such structures is a major component of any structural health monitoring (SHM) approach. This chapter performs corrosion damage diagnostics and prognostics on a miter gate structure using multiscale corrosion simulation models developed at micro- and mesoscales. The diagnostic process will integrate measurements from macroscale images and water levels for the damage localization and diagnostics. The prognostic models will use the detected corrosion damage data from a deep learning model to update parameters in corrosion initiation time distribution, propagate uncertainties across the multiscale simulations, and eventually, estimate the remaining useful life.