  The nuclear reaction induced by photon is one of the important tools in the
investigation of atomic nuclei. In the reaction, a target material is bombarded
by photons with high-energies in the range of gamma-ray energy range. In the
bombarding process, the photons can statistically be absorbed by a nucleus in
the target material. Then the excited nucleus can decay by emitting proton,
neutron, alpha and light particles or photons. By performing photonuclear
reaction on the target, it can be easily investigated low-lying excited states
of the nuclei. In the present work, ({\gamma}, n) photonuclear reaction
cross-sections on different calcium isotopes have been estimated by using
artificial neural network method. The method is a mathematical model that
mimics the brain functionality of the creatures. The correlation coefficient
values of the method for both training and test phases being 0.99 indicate that
the method is very suitable for this purpose.
