Using a database containing audio files of respiratory sound records of asthmatic patients and healthy patients, a method of computer-aided diagnostics based on the machine learning technique – creation of neural networks, has been developed. The database contains 952 records of respiratory sounds of asthma patients at different stages of the disease, aged from several months to 47 years, and 167 records of volunteers. Records were carried out with a quiet breathing at four points: in the oral cavity, above the trachea, on the chest, the second intercostal space on the right side, and at a point on the back.The developed method of computer-aided diagnostics allows diagnosing bronchial asthma with high reliability: sensitivity of 89.3%, specificity of 86%, accuracy of about 88% and Youden’s index of 0.753.The program learned once makes it possible to diagnose bronchial asthma with high reliability regardless of patient’s gender and age, a stage of disease, as well as the point of sound recording.The developed method can be used as an additional screening method for the diagnostics of bronchial asthma and serve as the basis for development of computer control methods, including remote control (telemedicine) of patient’s condition and the effectiveness of the applied drugs in real time.