ABSTRACT Background and Aims Alcohol consumption is an inherent feature of alcohol use disorder (AUD), and drinking characteristics may be diagnostically informative. This study had three aims: (1) to examine the classification accuracy of several drinking quantity/frequency indicators in a large representative sample of U.S. community adults; (2) to extend the findings to a clinical sample of adults; and (3) to examine potential sex differences. Design This retrospective study utilized receiver operating characteristic (ROC) curves to evaluate area under the curve (AUC). Optimal cut-offs were identified using the Youden Index. Diagnostic validity was evaluated using accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Measurements Index tests included measures of quantity/frequency (e.g., drinks/drinking day, largest drinks/drinking day, number of drinking days, and heavy drinking frequency). The reference standard was AUD status as determined via a clinical interview (community sample) or a symptom checklist (clinical sample). Setting and Participants Two samples were examined: A large, nationally representative random sample of U.S. community adults who reported past-year drinking ( N =25,778, AUD=20%) and a consecutive drinking clinical sample from a Canadian mental health and addictions inpatient treatment centre ( N =1,341, AUD=82%). Findings All drinking indicators performed much better than chance at classifying AUD (AUCs=0.60-0.92, p s<.0001). Heavy drinking frequency indicators performed optimally in both the community (AUCs=0.78-0.87; accuracy=0.72-0.80) and clinical (AUC=0.85-0.92; accuracy =0.77-0.89) samples. Collectively, the most discriminating drinking behaviors were heavy drinking episodes and exceeding NIAAA drinking low-risk guidelines. No substantive sex differences in optimal cut-offs or variable performance were observed. Conclusions Drinking patterns performed well at classifying AUD in both a nationally representative and large inpatient sample, robustly identifying AUD at rates much better than chance and above accepted benchmarks, with limited differences by sex. Findings broadly support the potential utility of quantitative drinking indicators as being diagnostically informative in clinical settings.