A predictive model for pitting corrosion in buried pipelines is proposed. The model takes into consideration the chemical and physical properties of the soil and pipe to predict the time dependence of pitting depth and rate. Maximum pit depths were collected together with soil and pipe data at more than 250 excavation sites over a three-year period. The time dependence of the maximum pit depth was modeled as dmax = κ(t − t0)ν, where t is the exposure time, t0 is the pit initiation time, and κ and ν are the pitting proportionality and exponent parameters, respectively. A multivariate regression analysis was conducted with dmax as the dependent variable and the pipeline age, and the soil and pipe properties as the independent variables. The dependence of κ and ν on the predictor variables was found for the three soil textural classes identified in this study: clay, clay loam, and sandy clay loam. The proportionality parameter κ was found to be primarily influenced by the redox potential, pH value, soil resistivity, and the dissolved ion concentrations. In contrast, the pitting exponent ν was found to be influenced mainly by the pipe-to-soil potential, water content, bulk density, and the pipe coating type. A real-life pipeline integrity assessment is used as a case study to illustrate the application of the proposed model and to show how it can have a positive impact on integrity management programs.