Parkinson’s disease (PD) produces several speech impairments in the patients. Automatic classification of PD patients is performed considering speech recordings collected in noncontrolled acoustic conditions during normal phone calls in a unobtrusive way. A speech enhancement algorithm is applied to improve the quality of the signals. Two different classification approaches are considered: the classification of PD patients and healthy speakers and a multi-class experiment to classify patients in several stages of the disease. According to the results it is possible to classify PD patients and healthy controls with a AUe of up to 0.87. This work is a step forward to the development of telemonitoring systems to assess the speech of the patients.