A phase-field-based reaction-diffusion corrosion model is developed to predict microbially influenced corrosion (MIC) in metal alloys, with a focus on anaerobic conditions and sulfate-reducing bacteria (SRB). The formulation couples microbial sulfate reduction, sulfate transport, electrochemical kinetics, material dissolution, and mechanical effects. Microbial activity is modelled using a Monod-type expression for sulfate consumption, whereas the mechano-chemical coupling is incorporated through an enhanced mobility relationship that captures the influence of mechanical fields on corrosion kinetics. The model is calibrated against experiments and shows strong agreement in predicting pitting kinetics under SRB activity. Sensitivity analyses quantify the competing roles of microbial kinetics, transport, and thermodynamic driving forces in governing corrosion behaviour. The capability of the formulation to capture both MIC-induced pitting and stress-assisted corrosion across multiple length scales is demonstrated through case studies that include microstructure-sensitive simulations and structural-scale coupling with a cathodic protection (CP) model. Results show that finer grain sizes reduce pitting severity but promote faster defect propagation under mechanical loading. At the structural scale, coupling with the CP model enables predictions of defect growth under varying electrochemical conditions and over engineering-relevant length scales, as exemplified with the analysis of an offshore wind turbine monopile. CP delays pitting and suppresses crack propagation, although its effectiveness diminishes as sacrificial anodes degrade. The framework provides a predictive and computationally efficient tool for assessing MIC-induced damage over extended times, with potential applications in the integrity and life assessment of metallic structures operating in aggressive microbial environments.

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