In the Department of Pathology and Laboratory Medicine, at the beginning of each month, the clinical managers use expert knowledge to assign pathologists to expected daily specimens based on the criteria of workload restrictions, clinical sub-specialties, and availability. Since the size of the pathologists’ assignment problem is large, finding a feasible assignment manually is a very time-consuming process that takes a number of iterations over a number of days to complete. Moreover, every time there is a need to make a revision, a new assignment needs to be developed taking into account all the above criteria. The goal of this research is to develop an optimization model and a decision support tool that will help with monthly staffing of pathologists based on the criteria outlined above. The developed model is rooted in the classical operations research assignment problem and it is extended to account for the following requirements: each pathologist should be assigned to a similar specimen type throughout a week; for a given pathologist, there should be a rotation of the specimen types between the weeks; and the clinical managers’ preferences in terms of assigning a particular specimen type to a particular pathologist on a specific day need to be considered. A monthly assignment model covering 36 pathologists and 26 specimen types was solved using IBM ILOG CPLEX Optimization Studio. It is embedded in a decision support tool that helps clinical managers to make staffing decisions. The decision support tool has been validated using data from The Ottawa Hospital (TOH).