For several years now Latvia’s bridges have not received necessary maintenance and repairs. As a result 56% of the country’s bridges are in poor or very poor technical condition [1]. One of the main problems is the early deterioration of reinforced concrete bridges. Lack of concrete bridge durability compared to the expected life of these structures is an issue of concern in most countries, where most development has taken place during the last century. Due to a lack of funds, optimal planning of maintenance and repair is becoming increasingly important; therefore it is necessary to develop methods of predicting the performance of reinforced concrete bridges in the future. To predict a bridge’s service life, it is necessary to model the interaction progression of environmental and bridge structure design factors. The environmental impact on a concrete bridge’s service life can be determined by estimating the values of the amount of deterioration and the corresponding environmental parameters. This research outlines a method of assessing the technical condition of concrete bridges with respect to the progression of reinforcement corrosion deterioration, taking into account different environmental and bridge design factors and thereby enabling the remaining service life of concrete bridges to be predicted. Service life is determined empirically, by assuming that the progression of deterioration does not change under identical environmental and bridge design factors. Deterioration and its degree are direct consequences of the interaction of environmental conditions and design factors at the micro level. Therefore, it is necessary to obtain data for the parameters that characterize these interactions in order to make accurate service life forecasts. The progression of deterioration at the micro level is described by deterioration models, and the parameters for these models cannot be acquired by visual inspection; detailed material investigation on site or at the laboratory is required. Some parameter values, depending on conditions, also are recommended in the literature [2], [3]. The surface level is characterized by environmental conditions that are constant over the whole or part of the defined surface, and are detectable by visual inspection. Environmental conditions that are considered constant at the surface level can be variable at the micro level. The deterioration preconditions at the surface level are defined by environmental conditions (precipitation, splashes, sunshine exposure, etc.) and bridge design factors (surface position, surface distance from the road, shape, cover depth, etc.). By determining the stage of deterioration for a structure affected by such various conditions, it is possible to identify the preconditions that characterize the progression of deterioration and calculate a bridge’s approximate service life. By using this data acquisition methodology, information on reinforcement corrosion deterioration has been collected from 120 bridges all over Latvia. None of the bridge structures studied have received repairs that would affect the development of continuous deterioration. The method presented in this paper evaluates the reinforcement corrosion deterioration in 10 stages and allows for systematic identification of the influence of different environmental and structural design factors on reinforced concrete bridge durability. The proposed method can be used to determine the reinforcement corrosion deterioration development parameter values in order to make forecasts on the service life of bridges with corresponding factor combinations. A factor combination and the stage of damage characterizes the actual interaction between environment and the specific bridge design, which can be similar to a variety of bridges and allows empirical residual lifetime predictions to be made. The method systemizes the information on reinforcement corrosion deterioration stages and the amount which can be acquired by visual bridge inspection, therefore lessening the subjective interpretation of bridge inspection information. The results of comparison show that with service life expectancy up to 100 years, the predicted result is similar to results obtained by experimental research. The proposed method of service life forecasting will help to improve maintenance planning, which in turn will reduce the expense of maintenance, repair and restructuring. The method will help engineers to better understand the nature of bridge deterioration, its significance and possible consequences. The method can also be employed in bridge design to find more optimal design solutions that ensure durability.