In manufacturing systems, lead time reduction can provide a strategic advantage, specifically when it means the elimination of non-value added waiting time. Queuing theory and Discrete Event Simulation (DES) are two methods commonly used to analyze lead time reduction efforts. Queuing models offer the advantage of fast analytical solutions, whereas DES analyses allow incorporation of high levels of system detail. There is great potential in the coordinated use of these methods. However, it is important to fully understand the assumptions and approximations of queuing theory as it is extended to increasingly realistic scenarios. Here, a novel formulation of queuing model is demonstrated for systems with both rework and process downtime. An emphasis is placed on the extensive testing of the queuing model vs. DES under a wide range of conditions, including various levels of rework rate, arrival variability, and process downtime. The queuing model proves to be effective at estimating lead time in all conditions examined.