Recently, the exhaled breath temperature has been proposed as a potential marker for the evaluation of airway inflammation in asthma. The purpose of this study was to verify the ability to distinguish asthmatics from normal controls by a dedicated detailed mathematical evaluation of the exhaled air curve. Analysis was performed in the different phases of the curve of exhaled temperature, i.e. the rate of temperature increase (Δe°T) and the mean plateau value. Principal components analysis (PCA) and artificial neural networks (ANNs) were used for the evaluation of the data in 90 asthmatic children and in 33 healthy age-matched controls. Both PCA and ANNs showed that a separation between patients and controls can be obtained only by the evaluation of the plateau phase of the curve, which better reflects the periphery of the airway.