The cyanobacterium Trichodesmium spp. can be an important ecological and biogeochemical component for both the coastal and open ocean ecosystems by way of its nitrogen fixation ability. However, information regarding its spatial and temporal distribution remains sparse. Trichodesmium has unique optical properties that should allow for its spectral signature to be detectable in satellite ocean color data sets. Here, a global data set of concurrent measurements of Trichodesmium abundance and radiometric reflectance was compiled and used to develop bio-optical models for Trichodesmium. The most robust global model related the water-leaving radiance signal to the identification of an occurrence of a Trichodesmium bloom above a threshold value of 3200 trichomes L-1. Using the in situ data set, this model is trained to successfully predict Trichodesmium blooms (~92%) while minimizing false positive retrievals (~16% of nonbloom observations). A validation of the approach applied to Sea-viewing Wide Field-of-view Sensor (SeaWiFS) ocean color imagery shows that the model correctly predicts 76% of the bloom occurrences of an independent validation data set of in situ Trichodesmium observations. Ultimately, maps of Trichodesmium bloom occurrence will provide a means of addressing the ecology of Trichodesmium and its contribution to new production of the world oceans.