Background and Purpose— Early prediction of clinical outcome after aneurysmal subarachnoid hemorrhage (aSAH) is still lacking accuracy. In this observational cohort study, we aimed to develop and validate an accurate bedside prediction model for clinical outcome after aSAH, to aid decision-making at an early stage. Methods— For the development of the prediction model, a prospectively kept single-center cohort of 1215 aSAH patients, admitted between 1998 and 2014, was used. For temporal validation, a prospective cohort of 224 consecutive aSAH patients from the same center, admitted between 2015 and 2017, was used. External validation was performed using the ISAT (International Subarachnoid Aneurysm Trial) database (2143 patients). Primary outcome measure was poor functional outcome 2 months after aSAH, defined as modified Rankin Scale score 4–6. The model was constructed using multivariate regression analyses. Performance of the model was examined in terms of discrimination and calibration. Results— The final model included 4 predictors independently associated with poor outcome after 2 months: age, World Federation of Neurosurgical Societies grade after resuscitation, aneurysm size, and Fisher grade. Temporal validation showed high discrimination (area under the receiver operating characteristic curve, 0.90; 95% CI, 0.85–0.94), external validation showed fair to good discrimination (area under the receiver operating characteristic curve, 0.73; 95% CI, 0.70–0.76). The model showed satisfactory calibration in both validation cohorts. The SAFIRE grading scale was derived from the final model: size of the aneurysm, age, Fisher grade, world federation of neurosurgical societies after resuscitation. Conclusions— The SAFIRE grading scale is an accurate, generalizable, and easily applicable model for early prediction of clinical outcome after aSAH.