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Offshore oil and gas operations are located in remote and often harsh marine environments. An offshore development can never be completely safe; however the degree of safety can be increased by selecting the optimum design, and developing proactive risk management strategies. This requires the identification and assessment of major risk contributors, which can be accomplished using quantitative risk assessment techniques. Dynamic failure assessment is a new approach in process safety management, which enables the real time failure analysis of a process. This approach uses Bayesian and joint probability theories to develop a predictive failure model for a given process. As a process proceeds and generates incidents and accident precursors, the accident occurrence probability is predicted. This paper presents a methodology based on the concept of dynamic failure assessment and its use in revising the risk profile for a process system based on accident precursor data modeling. An event tree is formed for a given abnormal event. Subsequently, using accident precursor data from the facility prior and posterior failure probabilities of events are calculated. A predictive model is developed using joint probability theory. Accident likelihood is combined with consequence analysis results to estimate posterior risk profile. Application of the proposed methodology is demonstrated on a process in an offshore process facility.