To create and verify a scoring system for identifying patients with bronchiectasis at risk of exacerbations. Derivation of the scoring system used data from a retrospective cohort study enrolling 228 patients with bronchiectasis. Multivariable logistic regression analysis was performed to identify independent predictors associated with exacerbations. β-coefficients derived from the independent predictors in our logistic regression model were applied to create a scoring system (Total score was 8). The scoring system was then validated in a prospective cohort enrolling 334 patients with bronchiectasis. The derivation study showed that age ≥ 60 years (OR=2.583, 95%CI: 1.188-5.613), BMI<18.5 kg/m(2) (OR=2.991, 95%CI: 1.112-8.042), high medical research council dyspnea score (OR=7.905, 95%CI: 4.288-8.309), Pseudomonas aeruginosa colonization (OR=3.227, 95%CI: 1.041-9.004), the lobes involved on high-resolution computed tomography≥3 (OR=3.179, 95%CI: 1.449~6.976), prior intensive care unit admissions (OR=2.499, 95%CI: 1.301-4.801), and FEV1<50% predicted(OR=2.497, 95%CI: 1.421-5.080) were the independent predictors associated with exacerbations. The scoring system predicted exacerbations with an area under the receiver operator characteristic curve (AUC) of 0.79 (95% confidence interval, 0.74-0.84). In the validation cohorts, the total score ranged 0 to 6. There was significant difference in exacerbation frequency and quality of life between patients classified as low(0-2), intermediate(3-4), and high(5-8) risks by the scoring system (P<0.05). A higher score was associated with higher risk of exacerbations and poorer quality of life. Our scoring system was an efficient clinical predictive tool to identify patients with bronchiectasis at risk of exacerbations. It may be useful for early prevention of bronchiectasis exacerbations and for proper management.