Hurricane Dorian formed on 24 August 2019 from a tropical wave and developed into a Category 5 hurricane on 1 September 2019 before making landfall in the Bahamas (Avila et al. 2020). The impacts on the Bahamas were extreme, including rainfall totals over 0.5 m in the region (Avila et al. 2020). This was on the heels of the recent damaging North Atlantic hurricanes of 2017 and 2018, which impacted various regions with different combinations of hazards (Klotzbach et al. 2018a; Avila 2019). Tropical cyclones are very costly natural disasters (Klotzbach et al. 2018b) due to a diverse set of impacts, including high winds, extreme rainfall, storm surge, and fresh and/or saltwater flooding. Previous work has explored the potential impact of climate change, both in the past and projected into the future, on these hazards (e.g., Knutson et al. 2010, 2019, 2020; Christensen et al. 2013; Walsh et al. 2016). A recent review by Knutson et al. (2020) estimates that the global mean near-storm rainfall increases at about 7% per 1°C. Significant advances have been made in attribution frameworks to help quantify the effect of climate change on individual hurricanes. Investigations of individual storms using various attribution methodologies suggest that changes in rainfall can exceed the Knutson et al. (2020) estimate, although there are uncertainties associated with the use of different rainfall metrics (e.g., Risser and Wehner 2017; van Oldenborgh et al. 2017; Emanuel 2017; Wang et al. 2018; Keellings and Hernández Ayala 2019). Here we apply a hindcast attribution methodology to Hurricane Dorian previously developed and tested for Hurricane Florence (Reed et al. 2020), Typhoon Haiyan (Wehner et al. 2019), and numerous other tropical cyclones (Patricola and Wehner 2018) that focuses on storm rainfall due to confidence in the model’s ability to simulate precipitation processes.