The variability of the breath-to-breath breathing pattern, and its alterations in disease, may hold information of physiologic and/or diagnostic value. We hypothesized that this variability arises from the way that noise is processed within the respiratory feedback control loop, and that pathologic alterations to specific components within the system give rise to characteristic alterations in breathing pattern variability. We explored this hypothesis using a computational model of the respiratory control system that integrates mechanical factors, gas exchange processes, and chemoreceptor signals to simulate breathing patterns subject to the influences of random variability in each of the system components. We found that the greatest changes in the coefficient of variation (CV) of both breathing amplitude and timing were caused by increases in lung resistance and impairments in gas exchange, both common features of pulmonary disease. This suggests that breathing pattern variability may reflect discernible deterministic processes involved in the control of breathing. © 2019 Elsevier Ltd