Currently used asset management programs by various state departments of transportation (DOT) rely typically on field-based condition assessments (periodic inspections and deterioration curves) of bridges for planning repair and maintenance activities. However, field inspections are labor intensive and can be subjective. Furthermore, visual inspections rely on visible signs of deterioration on the exterior surface of a bridge (e.g., corrosion stains and cracks) and may miss severe localized deterioration hidden inside concrete, which could incur significant repair costs in the future. On the other hand, physics-based models rely on simulating the underlying deterioration mechanisms for predicting future deterioration. Several parameters used in physics-based models are often based on extrapolating laboratory data that is not representative of field conditions. Furthermore, the outputs of physics-based deterioration model (e.g., rebar area loss) cannot be translated to condition ratings and are therefore unusable in asset management programs of state DOTs. For addressing these limitations, this research aims to (1) determine a rational basis for linking the outputs of a physics-based corrosion model to field-based condition ratings, and (2) calibration of input parameters of physics-based corrosion model based on deterioration curves obtained from field-based assessments. This report presents a systematic procedure for achieving these two aims. An example bridge column owned by New York State DOT is used to demonstrate the procedure. Links between the surface crack width and spalling and bridge element condition rating were established based on the interpretation of condition ratings. Inputs of the corrosion model were calibrated by matching the crack widths and spalling interpreted from deterioration curves with the outputs of the physics-based corrosion model. This project is expected to improve asset management by supplementing the field-based condition assessments with physics-based deterioration models.