ABSTRACT Critical Care is a medical specialty which addresses the life-saving and lifesustaining management of patients at risk of imminent death. The number of Intensive Care Unit (ICU) beds has an impact on patient’s prognosis. This paper aims to determine the optimal number of ICU beds to reduce patient’s waiting time. Time series was applied to predict demand making use of information on the daily patient’s requests for ICU beds to obtain a demand forecast by means of exponential smoothing and Box-Jenkins models, which provided the input of a Queuing model. The outputs were the optimal number of ICU beds, in different scenarios, based on demand rate and patient’s length of stay (LOS). A maximum waiting time in the queue of 6 hours was proposed and compared to government recommendation (118-353 beds). The need for ICU beds varied from 345 to 592 for a 6-hour waiting time (for a LOS of 6.5 to 11.2 days, respectively). The results show that managing demand and discharge timing could control the queue. Moreover, they also suggest that the current recommendation is inadequate for the demand.