A preliminary analysis on the power of Machine learning in tagging hadronic jets as either quark jets or gluon jets. We know boosted objects creates jets with a peculiar structure and we are able to separate them in category due to kinematical cuts or polarity of particles inside jets (N-subjettines, energy correlation functions and others) but the problem of classification of gluon and quark jets is still an open and crucial problem for LHC data analysis.