Over the last five decades, there have been several phases of interest in the so-called hydrogen economy, stemming from the need for either energy security enhancement or climate change mitigation. None of these phases has been successful in terms of a major market development, mainly due to the lack of cost competitiveness and partially due to technology readiness challenges. Nevertheless, a new phase has begun very recently, which despite holding original objectives has the new motivation to be fully green, i.e. based on renewable energy. This new movement has already initiated bipartisan cooperation of some energy importing countries and those with abundant renewable energy resources and supporting infrastructure. One key challenge in this context is the diversity of pathways for the (national and international) export of non-electricity renewable energy. This poses another challenge, that is the need for an agnostic tool for comparing various supply chain pathways fairly while considering various techno-economic factors such as renewable energy sources, hydrogen production and conversion technologies, transport, and destination markets, along with all associated uncertainties.This paper addresses the above challenge by introducing a probabilistic decision analysis cycle methodology for evaluating various renewable energy supply chain pathways based on the hydrogen vector. The decision support tool is generic and can accommodate any kind of renewable chemical and fuel supply chain option. As a case study, we have investigated eight supply chain options composed of two electrolysers (alkaline and membrane) and four carrier options (compressed hydrogen, liquefied hydrogen, methanol, and ammonia) for export from Australian ports to three destinations in Singapore, Japan, and Germany. The results clearly show the complexity of decision making induced by multiple factors, and that the preferred supply chain combination (electrolyser technology, green energy carrier) in terms of least cost strongly depends on whether the expected levelized cost of hydrogen (ELCOH) or the expected levelized cost of energy (ELCOE) is used as a decision criterion. For instance, with ELCOH for the case study, under the given input parameters, the Ammonia combination with alkaline electrolysers (AE-NH3) becomes the least-cost supply chain option for Singapore, Japan, and Germany with values of 8.60, 8.78 and 9.63 $/kgH2, respectively. This leaves liquid hydrogen (with alkaline electrolysers) as the second-best supply chain route, with ELCOH values of 9.05, 9.39 and 10.70 $/kgH2, respectively. However, with ELCOE, methanol (with alkaline electrolysers) becomes the preferred supply chain path for all destinations, and liquid hydrogen (with alkaline electrolysers) keeps its place as the second-best alternative.