In　the　age　of　social　media,　posting　attractive　mugshots　is　commonplace,　leading　to　an　urgent　need　for　automatic　facial　beautification　techniques.　To　better　meet　the　esthetic　preferences　of　users,　we　devise　a　customized　automatic　face　beautification　task　that　can　retouch　the　face　adaptively　to　match　the　user-entered　target　score　whilst　preserving　the　ID　information　as　much　as　possible.　To　accomplish　this　task,　we　propose　a　Human　Esthetics　Guided　StyleGAN　Inversion　method　to　retouch　each　face　in　the　embedding　space　using　StyleGAN　inversion.　This　process　is　guided　by　a　pre-trained　facial　beauty　prediction　model　that　measures　the　difference　between　the　target　score　and　the　predicted　score　of　the　retouched　face.　We　conduct　extensive　experiments　on　various　faces　with　different　attributes,　where　the　experimental　results　show　that　our　method　achieves　the　competitive　performance,　both　in　terms　of　visual　effect　and　the　proposed　criterion.　©　2023　IEEE.