This study proposes a decision-making process for the maintenance of asphalt overlays on concrete bridge decks based on interface conditions evaluated by a non-destructive method. Field data, including crack ratio, rutting depth, surface roughness (IRI, international roughness index), and relative permittivity, were used as variables to evaluate the asphalt bridge-deck pavement conditions at twelve locations (total length of 5268 m) using a vehicle-type automated digital road scanner. The relative permittivities of the concrete bridge decks were measured using a ground penetrating radar scanner on the surfaces of the asphalt layers, and the deck conditions were verified after the removal of the asphalt layers. Through field investigation, 1312 data sets were collected, and statistical analyses were performed to identify characteristics of the variables for evaluating the bridge-pavement condition. Based on the field data and Seoul pavement index formula, the bridge pavement index, which can reflect the condition of the concrete bridge deck beneath the asphalt layer, was developed. Furthermore, a decision-making tree was developed to select appropriate rehabilitation methods depending on various distress types and seriousness, as determined by field data.