Context. Humpback whale (Megaptera novaeangliae; HW) populations have been recovering from whaling but are now facing threats such as ocean warming and changes in habitat suitability. There is uncertainty over whether opportunistic observations can produce reliable species distribution models (SDMs) and adequately inform conservation management. Aims. To compare SDMs for HW in the Great Barrier Reef Marine Park (GBRMP) based on different opportunistic sightings datasets and evaluate the impact different sources of opportunistic data have on our understanding of HW habitat relationships. Methods. Maxent was used to create predictive models for HWs' distributions. Models were compared to evaluate disparities and predictive capabilities. Key results. Distinct environmental variables [bathymetry, distance to the coast] were identified as the most relevant for each SDM. The best-fitting model diverged from an existing model, with HW distribution predicted to be closer to shore. Areas with the highest habitat suitability were concentrated in the north-eastern coastal region across all our models. Conclusions. This study demonstrates that, with careful application and consideration, citizen science data can enhance our understanding of HW distributions and contribute to their conservation. The research underlines the importance of embracing diverse data sources in species distribution modelling, despite the challenges posed.