Abstract
**Abstract**
Maritime law has traditionally assessed liability through an outcome-oriented framework in which legal responsibility crystallises only after damage, collision, or casualty has occurred. The emergence of digital twin technology challenges this foundational assumption by enabling ships to predict structural failures, navigational hazards, and operational risks before they materialise. This article examines whether the availability of credible predictive intelligence should reshape the legal standard of prudence under contemporary maritime law. Through a doctrinal analysis of the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW), the International Regulations for Preventing Collisions at Sea (COLREGs), principles of negligence, and the evolving regulatory treatment of maritime technologies, the article argues that digital twins introduce a distinct category of "predictive knowledge" that existing legal frameworks neither expressly recognise nor adequately regulate.
Rather than advocating automated decision-making or replacing human judgment, the article contends that predictive technologies alter the evidentiary and normative foundations of maritime responsibility by documenting what decision-makers knew, when they knew it, and how they responded. It proposes that the increasing reliability of digital twins may gradually shift judicial and regulatory inquiry from retrospective causation towards prospective decision quality, where the reasonableness of ignoring a credible warning becomes legally significant even if no casualty ultimately occurs. This emerging paradigm challenges the conventional equation between harm and liability and suggests that enhanced technological foresight may generate correspondingly enhanced professional responsibility. The article concludes that the future development of maritime law will depend not merely upon allocating liability after accidents but upon redefining prudent seamanship in an era where intelligent systems can perceive foreseeable risks before human operators.