Objective To explore medical equipment allocation with considerations on randomly distributed and dynamic injury conditions by analyzing injury conditions transition and medical equipment stochastic service process.Methods A casualty array change model was established by injury conditions evolution analysis,Poisson process and Markov chain.Medical equipment stochastic service processes in medical facilities were probed,and the service rules were constructed.Expert investigation was carried out to acquire conditions transition indexes and to determine the vectors for conditions transition without manual intervention and their changes after treatment,then simulation tools were used to optimize medical equipment allocation.Results The emergency treatment table in some field medical station was considered as the subject,and the optimum allocation was proposed for emergency treatment table with practical data and simulation calculation.Conclusion The emergency treatment table allocation proposed was similar to the actual one in the medical station.Markov-process-based medical equipment allocation responses injury conditions changes and the fluctuation of treatment sequence,which has the result reliable and the method versatile and practical,and lays a foundation for medical equipment allocation and optimization.