Invasive species from the Suez Canal, also named "Lessepsian species", often have an ecological and financial impact on marine life, fisheries, human well-being and health in the Mediterranean Sea. Among these, the silver-cheeked toad-fish Lagocephalus sceleratus (Gmelin, 1789) has rapidly colonised the eastern Mediterranean basin and is currently moving westwards. This pufferfish has a highly opportunistic behaviour, it attacks fish captured in nets and lines and seriously damages fishing gears and catch. It is a highly-toxic species with no immediate economic value for the Mediterranean market, although it currently represents 4% of the weight of the total artisanal catches. Consequently, the possible effects on Mediterranean fisheries and health require to enhance our understanding about the future geographical distribution of this pufferfish in the whole basin. In this paper, an overall habitat suitability map and an effective geographical spread map for L. sceleratus at Mediterranean scale are produced by using cloud computing-based algorithms to merge seven machine learning approaches. Further, the potential impact of the species is estimated for several Mediterranean Sea subdivisions: The major fishing areas of the Food and Agriculture Organization of the United Nations, the Economic Exclusive Zones, and the subdivisions of the General Fisheries Commission for the Mediterranean Sea. Our results suggest that without an intervention, L. sceleratus will continue its rapid spread and will likely have a high impact on fisheries. The presented method is generic and can be applied to other invasive species. It is based on an Open Science approach and all processes are freely available as Web services.