Alcohol　misuse　is　associated　with　altered　punishment　and　reward　processing.　Here,　we　investigated　neural　network　responses　to　reward　and　punishment　and　the　molecular　profiles　of　the　connectivity　features　predicting　alcohol　use　severity　in　young　adults.　We　curated　the　Human　Connectome　Project　data　and　employed　connectome-based　predictive　modeling　(CPM)　to　examine　how　functional　connectivity　(FC)　features　during　wins　and　losses　are　associated　with　alcohol　use　severity,　quantified　by　Semi-Structured　Assessment　for　the　Genetics　of　Alcoholism,　in　981　young　adults.　We　combined　the　CPM　findings　and　the　JuSpace　toolbox　to　characterize　the　molecular　profiles　of　the　network　connectivity　features　of　alcohol　use　severity.　The　connectomics　predicting　alcohol　use　severity　appeared　specific,　comprising　less　than　0.12%　of　all　features,　including　medial　frontal,　motor/sensory,　and　cerebellum/brainstem　networks　during　punishment　processing　and　medial　frontal,　fronto-parietal,　and　motor/sensory　networks　during　reward　processing.　Spatial　correlation　analyses　showed　that　these　networks　were　associated　predominantly　with　serotonergic　and　GABAa　signaling.　To　conclude,　a　distinct　pattern　of　network　connectivity　predicted　alcohol　use　severity　in　young　adult　drinkers.　These　＂neural　fingerprints＂　elucidate　how　alcohol　misuse　impacts　the　brain　and　provide　evidence　of　new　targets　for　future　intervention.