The Fermi/LAT telescope is an efficient blazar-detector in the MeV/GeV range. More than 1100 (900) blazars detected above 100 MeV (10 GeV) are clearly associated to BL Lacertae or Flat Spectrum Radio Quasar objects in the Fermi/LAT 3FGL catalogue. This number could significantly increase if multi-wavelength counterparts could be identified for the 573 3FGL blazars with unknown type, or even for the 1010 3FGL unassociated sources which are thought to be dominated by blazars, at least at high galactic latitude. Unfortunately, the size of the Fermi/LAT error box makes multi-wavelength follow-ups difficult.
We propose a method to associate "blazar-like" infrared counterparts, having coordinates with a precision of a few arcseconds, to Fermi/LAT blazars and unassociated sources. To reach this goal, we built machine-learning classifiers based on the statistical differences of magnitude measurements obtained by the WISE satellite, between a sample of well-identified infrared blazars and samples of other types of infrared sources located in regions of the sky where no known blazar is present. We provide a list of potential infrared counterparts for 3FGL blazar candidates, along with the associated number of expected false positives. This study contributes to increase the number of well-identified extragalactic blazars and also provides promising blazar targets for the Cherenkov Telescope Array.