Bronchiectasis is a multidimensional disease and, therefore, its severity or prognosis cannot be adequately quantified by analysing one single variable. The objective of the present study was to develop a multidimensional score that classifies the severity of bronchiectasis according to its prognosis. This is an observational multicentre study including 819 patients diagnosed with non-cystic fibrosis bronchiectasis using high-resolution computed tomography. 397 subjects were selected at random to construct the score while the remaining 422 were used for its validation. The outcome was 5-year all-cause mortality after radiological diagnosis. A logistic regression analysis was used to select the variables included in the final score.The final seven-point score incorporated five dichotomised variables: forced expiratory volume in 1 s % predicted (F, cut-off 50%, maximum value 2 points); age (A, cut-off 70 years, maximum value 2 points); presence of chronic colonisation by Pseudomonas aeruginosa (C, dichotomic, maximum value 1 point); radiological extension (E, number of lobes affected, cut-off two lobes, maximum value 1 point); and dyspnoea (D, cut-off grade II on the Medical Research Council scale, maximum value 1 point) to construct the FACED score. The validation cohort confirmed the score's validity.We conclude that this easy-to-use multidimensional grading system proved capable of accurately classifying the severity of bronchiectasis according to its prognosis. @ERSpublications An easy-to-use multidimensional grading system accurately classifies bronchiectasis severity according to prognosis