Satellite and reanalysis data over 20 years (2003‒2022) are used to study how the estimated inversion strength (EIS), other known thermodynamic variables, dust aerosols (DAs) and biomass-burning aerosols (BBAs) affect the monthly variations of marine stratocumulus (MSc) to the west of Canary Islands and Namibia. Although EIS is thought to be the main predictor of low-cloud cover (LCC), the seasonal cycles of EIS and LCC differ significantly in the Canary MSc region. In linear regression models, adding DA optical depth as a predictor significantly improves the prediction of LCC across all seasons and almost everywhere in the region compared to using EIS alone. In fact, DAs contribute more than EIS to the LCC maximum in boreal summer, reducing the error by up to 11%. In this season, large amount of DAs are transported by the African Easterly Jet from the Sahara to the Canary MSc region. DAs can increase LCC as they are effective cloud condensation nucleii (CCN). Other known thermodynamic predictors of LCC can reduce the error, but by far less effectively than DAs. BBAs also improve the prediction of LCC in the region, but less so than DAs, suggesting that BBAs are less effective as CCN. Our results indicate the insufficiency of EIS as a predictor of LCC, particularly in the Canary MSc region, a limitation that aerosols as CCN help to address.