The Beaufort Sea has experienced significant sea ice retreat in recent decades, driven by both thermodynamic and dynamic processes. This study investigates the drivers and predictability of summer sea ice retreat in the Beaufort Sea by integrating an ocean–sea ice model with satellite-derived sea ice concentration data and atmospheric reanalysis products. Model diagnostics from 1994 to 2019 reveal that thermodynamic processes dominate annual sea ice loss (approximately 90%), with vertical heat flux accounting for roughly 85% of total oceanic heat input. The summer sea ice minimum area and the day of opening, derived from either model results and satellite observations, have a strong correlation with R² = 0.60 and R² = 0.77, respectively, enabling regression equations based solely on remote sensing data. Further multiple linear regression incorporating preceding winter (January to April) accumulated temperature and easterly wind yields moderately robust forecasts of minimum sea ice area (R² = 0.49) during 1998–2020. Additionally, analysis of reanalysis wind data shows that the timing of minimum sea ice area is significantly influenced by the frequency and intensity of sub-seasonal easterly wind events during melt season. These results demonstrate the critical importance of remote sensing in monitoring Arctic sea ice variability and enhancing seasonal prediction capability under a rapidly changing climate.