Crowding is correlated to many adverse outcomes in Emergency Departments (EDs), e.g., long waiting times. As a part of the solution against crowding, many hospitals utilize triage algorithm to rapidly sort patients according to the severity of their injury or illness. Decision making is a crucial aspect of the triage process due to the increased concern of improving productivity at the ED and the need for reducing the waiting time for patients who need immediate medical intervention. To improve the decision making in healthcare systems, many researchers have implemented different tools and models from various fields. In this paper, we are utilizing the Group Technology (GT) concept to sort and prioritize patients in ED. The methodology identifies patient groups according to patient characteristics, i.e., age, gender, pain level, and vital signs, and the processing requirements. Discrete Event Simulation (DES) is used to investigate the performance of the newly developed algorithm. The developed algorithm outperformed the currently used Emergency Severity Index (ESI) algorithm in terms of the percentage of tardy patients and their associated risk.