AIM: To identify surrogate clinical biomarkers for profiling the eosinophilic status of an individual patient over induced sputum analysis. METHODS: We conducted a cross-sectional study on 100 asthmatic patients whose induced sputum was successfully collected. Subjects were further classified into either EA or NEA based on whether the percentage of sputum eosinophil count (SEC%) was≥3%. Demographic and clinical data were collected, including basic information, routine blood tests, lung function tests, bronchodilator reversibility tests, fractional exhaled nitric oxide (FeNO), the Asthma Control Test (ACT) and the Asthma Control Questionnaire (ACQ). All variables significantly associated with EA were candidates for multivariate logistic regression analysis. A scoring system presented as a nomogram for the prediction of EA was developed. RESULTS: In the univariate analysis, compared with NEA subjects, those with EA were of older age and had worse asthma control and lung function in addition to higher values of blood eosinophils, serum IgE and FeNO. Multivariable logistic regression analysis revealed that age, FeNO, serum IgE and blood eosinophil count (BEC) were identified as independent risk factors for eosinophilic asthma, which were all included in the nomogram. CONCLUSION: A combination assessment including age, FeNO, serum IgE and BEC could be applicable to clinicians in identifying eosinophilic asthma and is easier, faster, more inexpensive and more readily available than the induced sputum test.