  Blazars and in particular the subclass of high synchrotron peaked Active
Galactic Nuclei are among the main targets for the present generation of
Imaging Atmospheric Cherenkov Telescopes (IACTs) and will remain of great
importance for very high-energy $\gamma$-ray science in the era of the
Cherenkov Telescope Array (CTA). Observations by IACTs, which have relatively
small fields of view ($\sim$ few degrees), are limited by viewing conditions;
therefore, it is important to select the most promising targets in order to
increase the number of detections. The aim of this paper is to search for
unclassified blazars among known $\gamma$-ray sources from the Fermi Large Area
Telescope (LAT) third source catalog that are likely detectable with IACTs or
CTA. We use an artificial neural network algorithm and updated analysis of
Fermi-LAT data. We found 80 $\gamma$-ray source candidates, and for the
highest-confidence candidates, we calculate their potential detectability with
IACTs and CTA based on an extrapolation of their energy spectra. Follow-up
observations of our source candidates could significantly increase the current
TeV source population sample and could ultimately confirm the efficiency of our
algorithm to select TeV sources.
