Objective: To develop a method to distinguish reversible cerebral vasoconstriction syndrome (RCVS) from other large/medium-vessel intracranial arteriopathies., Methods: We identified consecutive patients from our institutional databases admitted in 2013-2017 with newly diagnosed RCVS (n = 30) or non-RCVS arteriopathy (n = 80). Admission clinical and imaging features were compared. Multivariate logistic regression modeling was used to develop a discriminatory score. Score validity was tested in a separate cohort of patients with RCVS and its closest mimic, primary angiitis of the CNS (PACNS). In addition, key variables were used to develop a bedside approach to distinguish RCVS from non-RCVS arteriopathies., Results: The RCVS group had significantly more women, vasoconstrictive triggers, thunderclap headaches, normal brain imaging results, and better outcomes. Beta coefficients from the multivariate regression model yielding the best c -statistic (0.989) were used to develop the RCVS 2 score (range -2 to +10; recurrent/single thunderclap headache; carotid artery involvement; vasoconstrictive trigger; sex; subarachnoid hemorrhage). Score ≥5 had 99% specificity and 90% sensitivity for diagnosing RCVS, and score ≤2 had 100% specificity and 85% sensitivity for excluding RCVS. Scores 3-4 had 86% specificity and 10% sensitivity for diagnosing RCVS. The score showed similar performance to distinguish RCVS from PACNS in the validation cohort. A clinical approach based on recurrent thunderclap headaches, trigger and normal brain scans, or convexity subarachnoid hemorrhage correctly diagnosed 25 of 37 patients with RCVS 2 scores 3-4 across the derivation and validation cohorts., Conclusion: RCVS can be accurately distinguished from other intracranial arteriopathies upon admission, using widely available clinical and imaging features., Classification of Evidence: This study provides Class II evidence that the RCVS 2 score accurately distinguishes patients with RCVS from those with other intracranial arteriopathies., (© 2019 American Academy of Neurology.)