Phytoplankton community is an important organism indicator of monitoring water quality, and accurately estimating its composition and biomass is crucial for understanding marine ecosystems and biogeochemical processes. Identifying phytoplankton species remains a challenging task in the field of oceanography. Phytoplankton fluorescence is an important biological property of phytoplankton, whose fluorescence emissions are closely related to its community. However, the existing estimation approaches for phytoplankton communities by fluorescence are inaccurate and complex. In the present study, a new, simple method was developed for determining the Chlorophytes, Chrysophytes, Cryptophytes, Diatoms, Dinoflagellates, and Prymnesiophytes based on the fluorescence emission spectra measured from the HOBI Labs Hydroscat-6P (HS-6P) in the Bohai Sea, Yellow Sea, and East China Sea. This study used single bands, band ratios, and band combinations of the fluorescence signals to test their correlations with the six dominant algal species. The optimal band forms were confirmed, i.e., X1 (i.e., fl(700), which means the fluorescence emission signal at 700 nm band) for Chlorophytes, Cryptophytes, Dinoflagellates, and Prymnesiophytes (R = 0.947, 0.862, 0.911, and 0.918, respectively) and X7 (i.e., [fl(700) + fl(550)]/[fl(550)/fl(700)], where fl(550) denotes the fluorescence emission signal at 550 nm band) for Chrysophytes and Diatoms (R = 0.893 and 0.963, respectively). These established models here show good performances, yielding low estimation errors (i.e., root mean square errors of 0.16, 0.02, 0.06, 0.36, 0.18, and 0.03 for Chlorophytes, Chrysophytes, Cryptophytes, Diatoms, Dinoflagellates, and Prymnesiophytes, respectively) between in situ and modeled phytoplankton communities. Meanwhile, the spatial distributions of phytoplankton communities observed from both in situ and fluorescence-derived results agreed well. These excellent outputs indicate that the proposed method is to a large extent feasible and robust for estimating those dominant algal species in marine waters. In addition, we have applied this method to three vertical sections, and the retrieved vertical spatial distributions by this method can fill the gap of the common optical remote sensing approach, which usually only detects the sea surface information. Overall, our findings indicate that the proposed method by the fluorescence emission spectra is a potentially promising way to estimate phytoplankton communities, in particular enlarging the profiling information.