Galaxy morphology is one of the most important parameters to understand the assembly and evolution of galaxies in the universe. The most used classification nowadays was proposed by Hubble (1926). This classification is based on the present of disks-, arms-, bulges-like structures, and is carried out mostly by eye identification. Thanks to the upcoming large telescopes and surveys, the new catalogues will contain millions of galaxies, making impossible to carry out a visual classification. Then, convolutional neural networks (CNN) start to play an important role to classify galaxies automatically. In this work I summarise the most recent results (including ours) using machine learning techniques to classify galaxies and future projects.