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In addition to the concerns around global climate changes, the population and urbanization growth have necessitated both academia and industrial sectors to investigate cleaner and sustainable energy resources. As a predominant renewable resource, wind energy has been widely adopted by different nations during the last decades because of its worldwide extraction availabilities and the existing knowledge achieved from aerospace industries. Offshore wind farms (OWFs) are already operational in many countries, including the UK, Germany, Denmark, and America. Australia can significantly benefit from energy production using wind technology, given the special available resources. However, amongst many challenges in developing a new power plant and its supply chain, a critical challenge is determining the optimal site location for establishing a wind farm. Many contributing factors and their associated uncertainties make this a complex decision-making problem. The present work objects to develop a decision-making framework based on reliable techniques to select the optimum site location for developing an OWF in Australia. The proposed framework is based on the Bayesian best-worst method, which can be used as a decision-support tool incorporating a range of contributing factors. The obtained results are a robust optimal ranking of the studied site locations, where the optimally ranked location is off the northeast coast of Tasmania close to Flinders Island where substantial wind resources are reported to be available for harnessing. • A framework to identify the optimal site for developing an offshore wind farm. • Bayesian best-worst method technique is mapped for offshore renewable energy domains. • Knowledge of experts from the offshore engineering, marine renewables and risk and decision analysis fields is elicited for optimal decision making. • An extensive set of decision criteria and their associated constraints are established for site selection of offshore wind farm in Australia. [ABSTRACT FROM AUTHOR]