Rationale　In　recent　years,　white　tea　has　become　increasingly　popular.　Some　merchants　confuse　the　age　of　white　tea　and　sell　poor-quality　products　for　profit.　Therefore,　it　is　necessary　to　provide　technical　support　for　product　authentication　and　valorization　in　white　tea　of　different　marked　ages.　Methods　Volatile　organic　compounds　(VOCs)　were　detected　by　proton　transfer　reaction　time-of-flight　mass　spectrometry　(PTR-TOF-MS)　and　identified　as　volatile　fingerprints.　PTR-TOF-MS　combined　with　multivariate　analysis　was　found　to　identify　white　tea　of　four　different　marked　ages　(1,　3,　5,　and　8　years)　for　authentication.　Principal　component　analysis　(PCA)　and　orthogonal　partial　least-squares　discriminant　analysis　(OPLS-DA)　were　used　as　classification　models　to　identify　key　volatile　metabolites.　Results　The　OPLS-DA　model　achieved　the　best　results　(96.67%,　96.67%,　96.67%,　and　96.67%　in　the　training　set　and　96.00%,　96.00%,　100%,　and　100%　in　the　prediction　set　for　1-year,　3-year,　5-year,　and　8-year　tea　samples,　respectively),　showing　that　PTR-TOF-MS　with　the　OPLS-DA　model　could　successfully　be　used　in　the　identification　of　white　tea　with　different　marked　ages.　Out　of　the　60　identified　VOCs,　26　volatile　materials　were　closely　correlated　with　tea　age　and　were　used　as　markers　to　discriminate　white　tea　of　different　ages.　Conclusions　PTR-TOF-MS　coupled　with　multivariate　analysis　could　be　applied　for　quality　evaluation　of　tea　products　of　different　ages　and　provided　a　feasible　technical　support　for　product　authentication　and　valorization　in　white　tea　of　different　marked　ages.