This paper suggests a novel analytical model to predict average issue rate of both in-order and out-of-order issue policies. Most of previous works have employed only simulation methods to measure the instruction-level parallelism for performance. However these methods cannot disclose the cause of the performance bottle-neck. In this paper, the proposed model takes into account such factors as issue policy, instruction-level parallelism, branch probability, the accuracy of branch prediction, instruction window size, and the number of pipeline units to estimate the issue rate more accurately. To prove the correctness of the model, extensive simulations were performed with Intel 80386/80387 instruction traces. Simulation results showed that the proposed model can estimate the issue rate accurately within 3-10% differences. The analytical model and simulations show that the out-of-order issue can improve the superscalar performance by 70-206% compared to the in-order issue. The model employs parameters to characterize the behavior of programs and the structure of superscalar that cause performance bottle-neck. Thus, it can disclose the cause of the disproportion in performance and reduce the burden of excess simulations that should be performed whenever a new processor is designed.