On the basis of our study of 55 samples collected during four cruises in the Yellow and Bohai Seas off the east coast of China (November 2014, August 2015, July 2016, and January 2017), we developed an algorithm for estimating the sea-surface density (SSD) using remote-sensing reflectance. Our results show that the multivariate linear regression model performs the best, with a determination coefficient of 0.70 and a mean absolute percentage error of SMAPE=3.49%. We used an independent dataset (27 in situ observations) to assess the performance of the model, yielding a validation result of SMAPE=3.27%. In addition, the sensitivity experiment of the model show that the observed fluctuation in the SMAPE values is <3%, indicating that our proposed model is relatively stable. Meanwhile, we applied our developed model to the geostationary ocean color imager (GOCI) satellite data recorded in July 2016 and successfully produced the SSD distribution pattern. The spatial characteristics show that the coastal waters, the central parts of the Bohai and Yellow Seas, and the waters off the northern Shandong Peninsula have relatively high SSD values, while relatively low values are distributed along the Qingdao coast.