Advanced maritime operations, such as remote pilotage, are vulnerable to new emergent risks due to increased system complexity and a multitude of interactions. Thus, maritime researchers this decade have combined Systems-Theoretic Process Analysis (STPA) and Bayesian Network (BN) to effectively manage these risks. Although these methods are effective in identifying hazards and analyzing risk levels, none of the STPA-BN studies provides a systematic process for selecting a cost-effective combination of risk control measures. Cost-benefit analysis is crucial for organizations to make informed risk-based decisions in allocating available resources for risk mitigation and achieve a balance between risk reduction (benefits) and costs associated with risk control measures. This study offers an innovative method of integrating the STPA-BN-Influence diagram for risk-based decision-making through a cost-benefit analysis. The model automatically evaluates the costs and benefits of all possible risk control options and proposes the optimum cost-effective solution. In the current study, the methodology is illustrated with a case study of remote pilotage operation, where 524,288 different risk control options (combinations of 19 risk control measures) are assessed to select an optimal risk control option. The case study results indicate that the proposed methodology is more significant when the number of risk control measures increases.