As hydrogen is a comparatively less safe fuel compared to conventional fuels such as gasoline and diesel, major accidents such as explosions and fires at hydrogen refuelling stations close to residential areas may lead to catastrophic consequences. It is difficult for a traditional quantitative risk analysis (QRA) method to efficiently assess human safety in a large region that includes not only the hydrogen refuelling station but also nearby commercial and residential areas. Therefore, a grid-based risk mapping method has been developed to enable efficient and detailed risk screening of such large areas. The target area is divided into a number of grids of an appropriate size, and a risk analysis is conducted for each grid. A total risk map can be depicted based on the risk evaluations of all grids, and a detailed risk assessment can then be applied to the most hazardous grids. Meanwhile, in order to consider multiple consequences and the complex interrelationships between risk factors, a Bayesian network (BN) model is implemented for the proposed method. At the same time, to reduce uncertainties caused by a shortage of data, three kinds of data—practical information, computational simulations and subjective judgements—are involved in the quantification of the proposed BN. The results from the case study show that the proposed method is capable of effectively conducting risk screenings for large and complex situations.