Objective To develop a risk prediction model for refractory pneumonia in children by combining early lung ultrasound features with clinical symptoms. Methods Data from 152 children with pneumonia hospitalized at Jiangsu Qidong Maternal and Child Health CareHospital between June 2024 and May 2025 were retrospectively collected. The children were divided according to whether the diagnostic criteria for refractory pneumonia were met into a refractory pneumonia group (n=50) and a non-refractory pneumonia group (n=102). Clinical characteristics and lung ultrasound findings were compared between groups. Independent predictors were identified using multivariable logistic regression analysis, and a nomogram-based prediction model for refractory pneumonia was developed. Model performance was evaluated using receiver operating characteristic curve, calibration curve, and decision curve analyses. Results Multivariable logistic regression analysis showed that fever (OR=4.193, 95%CI: 1.422-12.362) and lung ultrasound findings—area of pulmonary consolidation (OR=1.071, 95%CI: 1.012-1.133), pleural effusion (OR=3.794, 95%CI: 1.571-9.165), and signs of pneumothorax (OR=1.818, 95%CI: 1.014-3.261)—were independent predictors of refractory pneumonia (all P<0.05). The prediction model based on these four factors had a C-index of 0.772, and the area under the receiver operating characteristic curve was 0.772 (95%CI: 0.690-0.854), indicating good discrimination. Decision curve analysis showed favorable clinical utility when the threshold probability was between 15% and 80%. Conclusions A risk prediction model for refractory pneumonia in children mainly based on early lung ultrasound features shows good predictive performance and helps in the early assessment of refractory pneumonia risk.