Speech impairments are one of the earliest manifestations in patients with Parkinson’s disease. Particularly, articulation impairments related to the capability of the speaker to move the limbs and muscles of the vocal tract have been observed in the patients. Articulation deficits have been evaluated in the patients mainly using diadochokinetic exercises, which consist in the rapid repetition of syllables like /pa-ta-ka/. This study considered different features to model several aspects of the diadochokinetic exercises, including the capacity to start/stop the vocal fold vibration, the speech rate, and the regularity of the diadochokinetic task. Articulation features are combined with others that result from an empirical mode decomposition procedure, which have been recently used to model dysphonia in Parkinson’s patients. The features are used to classify Parkinson’s patients and healthy speakers, and to predict the dysarthria severity of the participants according to a clinical scale. According to the results, articulation features are able to classify the presence of the disease with an accuracy up to 76%, and to predict the dysarthria level of the speakers with a Spearman’s correlation of up to 0.68.