Seasonal ocean forecasts offer critical insights for marine resource management, particularly in regions like the Northeast Pacific where ecosystem variability can have profound impacts on marine life, fisheries, and coastal communities. Under NOAA’s Changing Ecosystems and Fisheries Initiative, we developed a seasonal ocean forecasting system for the Northeast Pacific based on the Modular Ocean Model version 6 (MOM6) ocean model coupled to the Sea Ice Simulator version 2 (SIS2) sea ice model and the Carbon, Ocean Biogeochemistry, and Lower Trophics (COBALT) biogeochemical model. The model domain extends from south of Baja California to the Chukchi Sea with ~10 km horizontal resolution. To evaluate forecast skill, we produced a 32-year set of retrospective forecasts with 10 ensemble members, four initializations per year, and lead times up to 12 months. Forcing for the forecasts was derived from the Geophysical Fluid Dynamics Laboratory's Seamless System for Prediction and Earth System Research (GFDL-SPEAR) global climate forecast system. Forecasts were assessed using ocean reanalyses and <em>in situ</em> observations, focusing on three ecologically- and societally-relevant variables: sea surface temperature, bottom temperature, and bottom oxygen concentration. Forecast skill varies by region, variable, and season, but generally remains high (anomaly correlation coefficient; ACC>0.5) for lead times of at least several months across all variables and regions. The downscaled forecasts reduce errors relative to the SPEAR global forecasts and in some cases increase ACC, while also enabling predictions of biogeochemical variables. These new forecasts compare favorably to previous downscaled ocean forecasts off the U.S. west coast, with increased ACC and small forecast errors that may be reduced further by future methodological changes. Routine real-time forecasts, available starting in October 2026, will support proactive decision making by managers, industry, and coastal communities.