The degradation of a concrete structure in northern climate is mainly due to the corrosion of steel reinforcements and cumulative damages from mechanical loading. Infrastructure managers heavily rely on ratings obtained from visual field surveys and the interpretation of inspection reports to predict the future structure states and to plan appropriate maintenance and replacement activities. In this paper, an effective structure management framework is proposed, combining information from on-site visual inspections and predictions from a nonlinear chloride transport model, to improve diagnostics for preventive maintenance. Meaningful predictions were obtained by using climatic data from neighboring weather stations and characterising the concrete transport properties with non-destructive tests. The chloride profiles from the model can be validated with core-drilled samples, if available. Predictions from the model were used to estimate the probability of the corrosion initiation and the condition states of the structural elements to complement the visual inspection observations. Finally, the ratings of each element were combined to obtain a global rating of the structure by considering the relative criticality of each element for the safety and the performance of the structure. The methodology was applied to a typical bridge in Montreal and demonstrated good agreement between the model predictions.