We present a new method to identify phytoplankton functional types (PFTs) in the Mediterranean Sea from ocean color data (GlobColour data in the present study) and AVHRR sea surface temperature. The principle of the method is constituted by two very fine clustering algorithms, one mapping the relationship between the satellite data and the pigments and the other between the pigments and the PFTs. The clustering algorithms are constituted of two efficient self‐organizing maps, which are neural network classifiers. We were able to identify and estimate the percentage of six PFTs: haptophytes, chlorophytes, cryptophytes, Synechococcus, Prochlorococcus, and diatoms. We found that these PFTs present a peculiar variability due to the complex physical and biogeochemical characteristics of the Mediterranean Sea: Haptophytes and chlorophytes dominate during winter and mainly in the western Mediterranean basin, while Synechococcus and Prochlorococcus dominate during summer. The dominance of diatoms was mainly observed in spring in the Balearic Sea in response to deep water convection phenomena and near the coastline and estuaries due to important continental inputs. Cryptophytes present a weak concentration in the Aegean Sea in autumn. The validation tests performed on in situ matchups showed satisfying results and proved the ability of the method to reconstruct efficiently the spatiotemporal patterns of phytoplankton groups in the Mediterranean Sea. The method can easily be applied to other oceanic regions.