Expert systems not only store knowledge about the problems they are given to solve, they are able to make inferences from their knowledge in the solving of specific tasks. They can explain their solutions and learn from their mistakes. An example of an expert system is one called MYCIN, which assists in antimicrobial selection for medical treatment. Expert systems are appropriate for the categorization of 911 emergency calls. Such systems would reduce reliance on the experience and training of the 911 call-taker, an important feature given the typically high turnover rate and inadequate training of such operators. An expert system would guide call-takers in prioritizing calls and obtaining sufficient information to help police service the call. The system could explain why it chose a particular sequence of questions for a particular call and how it assigned priority. The use of such a system is illustrated for family trouble calls and barking dog calls. The paper concludes with an investigation of the addition of an expert systems factor into an operations research algorithm called the Exact Hypercube Queuing Model, which is used to analyze problems of vehicle location and response district design in urban emergency services. Figures and 14 references.