Cutting costs and improving efficiency are perhaps two of the biggest concerns of businesses today. Companies have been turning to new and innovative approaches such as just-in-time inventory systems and crossfunctional work teams in this cost-cutting effort. Firms have also looked to experts in operations research and management science to streamline business systems and procedures. One specific area of operations research that many companies have utilized to both cut costs and improve efficiency is queuing theory. Queuing theory deals with the study of objects waiting in a line for a service. The objects could be anything from cars on an assembly line to people in the checkout lane at a grocery store. A number of queuing models have been developed to predict information about the line that could form based on a few pieces of data. The predictions from the model can then be used to compute dollar costs of different systems by determining operating costs and comparing them to customer costs. With the knowledge of different system costs, company management is able to implement the lowest cost system without actually building any of the systems. This thesis describes queuing research done at Helena Community Credit Union (HCCU) on customers using the walk-up counter of the financial institution and the application of a M/M/# queue model to the line. An M/M/# queuing model is a mathematical model describing a queuing system with exponentially distributed arrival and service times with a given number of servers. Many real world problems in queuing research and potential solutions to them were discovered and will be described in this paper. The paper concludes with the feasibility of using an MIMI# model for HCCU and banking in general.