  Pursuit of superconductivity in light-element systems at ambient pressure is
of great experimental and theoretical interest. In this work, we combine a
machine learning (ML) method with first-principles calculations to efficiently
search for the energetically favorable ternary Ca-B-C compounds. Three new
layered borocarbides (stable CaBC5 and metastable Ca2BC11 and CaB3C3) are
predicted to be phonon-mediated superconductors at ambient pressure. The
hexagonal CaB3C3 possesses the highest Tc of 26.05 K among the three compounds.
The {\sigma}-bonging bands around the Fermi level account for the large
electron-phonon coupling ({\lambda} = 0.980) of hexagonal CaB3C3. The ML-guided
approach opens up a way for greatly accelerating the discovery of new high-Tc
superconductors.
