Corrosion assessment is an integral part of predictive maintenance estimations. In such cases, a risk-based approach yields results that can easily be implemented. The results from deterministic (mechanistic or semi-empirical) corrosion models are valid for a “general” rate of dissolution based on the mass and charge balance of an exposed surface; however, they have a limited application in the quantitative assessment of corrosion-related damage. This work introduces a general stochastic algorithm for calculating the carbon dioxide (CO2)-related distribution of corrosion damage penetration at a given time interval, coupled with corrosion rates predicted by conventional deterministic models. The model is validated by directly comparing the simulation output with actual inspection results from several real cases. The results obtained indicate that the stochastic modeling of CO2 corrosion based on mechanistic principles allows the assessment of failure probability in a quantitative manner. Additionally, the application of a probabilistic approach in the evaluation of failure likelihood under active corrosion conditions readily simplifies the analysis of the combined effects, such as the inorganic scale deposition, flow, and chemical inhibition.