ObjectiveThe purpose of this study was to analyze the independent risk factors of malignant subpleural pulmonary lesions (SPLs) on B-mode ultrasound (US) images, to construct the combined predictive indicators, and to prospectively verify their predictive efficacy. MethodsA total of 336 patients with SPLs were included in the prospective study, of whom the single-center included patients between September 2019 and December 2019 were the development cohort (DC) (n = 219); Patients who were concurrently enrolled in three centers between January and February 2020 were the validation cohort (VC) (n = 117). The clinical features and B-mode US parameters were collected. Based on the DC, a combined predictive indicators model was developed using binary logistic regression. Then the discrimination was verified externally in the VC. The reference criteria were from the comprehensive diagnosis of clinical-radiological-pathological made by two senior respiratory physicians. ResultsThe combined predictive indicators model was finally constructed by five parameters: age, borderline, angle between the lesion border and thoracic wall, posterior echo of the lesion and invasion of the pleura. The fitting degree of the model was good (χ2 = 9.198, p = 0.326). The area under ROC curve of the model was 0.872 (DC) and 0.808 (VC), yielding a higher net benefit than individual risk factors. ConclusionThe combined predictive indicators are useful in the assessment of malignant SPLs and are a useful adjunct diagnostic tool, especially in primary healthcare settings in developing countries.