  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.
