This study , led by Mitch Bushuk, provides a comparison of September Arctic sea ice seasonal prediction skill across a diverse set of 34 dynamical and statistical prediction models, quantifying the state-of-the-art in the rapidly growing sea ice prediction research community. The authors find that both dynamical and statistical prediction models can skillfully predict September Arctic sea ice 0–3 months in advance on Pan-Arctic, regional, and local spatial scales. These results demonstrate that there are bright prospects for skillful operational seasonal predictions of Arctic sea ice and highlight a number of crucial prediction system design aspects to guide future improvements.