In the present paper, a methodological framework to move from risk assessment to resilience assessment is described. In order to demonstrate the practical capability of the outlined methodology reference is made to a LNG (Liquefied Natural Gas) bunker activity for a cruise ship. The focal point to assess the resilience of a system is the identification of precursor events, which refers to early detection of "weak" signals from the system during the operations. In order to identify the precursors, a large amount of data analytics is needed. By data processing, validation and analysis, it is possible to predict the behaviour of the system, thus catching the guide-words for a resilient performance. Starting from the operative steps of LNG bunker activity in the maritime field, various coupled Data Driven BNs can be built, which involve the probability of operational perturbations, and their updates based on the hard and soft evidences during the operation. Ship propulsion by LNG as a possible fuel (with dual fuel engines installed on board) implies to deepen safety issues that might be involved in the LNG bunkering operations. Not so many investigations are available in literature at present and the paper is aimed to frame the most significant critical aspects about this topic.