The nasal out-breath of persons with chronic nasal and/or paranasal infections may have characteristic strange odors, which in our experience are in most cases related to bacterial and/or fungal infections of the sinuses. The objective of the present study was to examine nasal out-breath samples from patients with chronic rhinosinusitis (CRS) (with or without polyposis) and healthy control volunteers using the electronic-nose (EN) technology. We developed a simple technique for collecting samples of nasal out-breath in disposable sterile plastic sacks with a tight closing seal. The principal component analysis correctly classified all individual EN patterns for CRS patients and misclassified 2 samples from the healthy controls (80.0% successful classification rate). The artificial neural network analysis correctly classified 60.0% of the patterns of both groups. We believe that the use of methodologies based on EN technology, combined with conventional clinical examinations, may improve the diagnosis of chronic rhinosinusitis.