Aiming　to　solve　the　problem　of　accurate　diagnosis　of　the　size　and　location　of　rolling　bearing　faults,　a　novel　quantitative　and　localization　fault　diagnosis　method　of　the　rolling　bearing　is　proposed　based　on　the　quantitative　mapping　model　(QMM).　The　fault　size　and　location　of　the　rolling　bearing　affect　the　impulse　type　and　the　modulation　degree　of　the　vibration　signal,　which　subsequently　changes　the　complexity　and　randomness　of　the　time-domain　distribution　of　the　vibration　signal.　According　to　the　relationship　between　the　multiscale　permutation　entropy　(MPE)　of　the　vibration　signal　and　rolling　bearing　fault　size,　an　average　MPE　(A-MPE)　index　is　proposed　to　establish　linear　and　nonlinear　QMMs　through　the　regression　function.　The　proper　QMM　is　selected　through　the　error　rate　of　fault　size　prediction　to　achieve　a　quantitative　fault　diagnosis　of　the　rolling　bearing.　Due　to　the　mathematical　characteristics　of　the　QMM,　the　localization　fault　diagnosis　is　realized.　The　multiscale　morphological　filtering　(MMF)　method　is　also　introduced　to　extract　the　time-domain　geometric　feature　of　the　fault　bearing　vibration　signal　and　to　improve　the　QMM　accuracy　of　the　fault　size　prediction.　The　results　show　that　the　QMM　has　a　great　effect　on　the　quantitative　fault　size　prediction　and　localization　diagnosis　of　the　rolling　bearing.