The efficient use of public funds for the structural integrity of bridge networks requires the implementation of an effective Bridge Management System (BMS). However, for long-term planning strategies in current asset management practice, there are some fundamental shortcomings associated with the health status of bridge elements. Although extensive research have been carried out to improve the overall quality of BMS outcomes, existing deterministic and probabilistic/stochastic deterioration modelling techniques are still limited in scope and application. This is attributable to a number of reasons including the lack of usable condition rating data due to late uptake in BMS implementation, and incompatible inspection records format. The situation is further aggravated by the randomness of data distribution related to various maintenance history and inconsistent bridge inspection processes.