1. A method, in an information handling system comprising one or more processors and a memory, of predicting system performance, the method comprising: identifying a non-linear Queuing Network Model (QNM) corresponding to an information technology (IT) environment, wherein the non-linear QNM includes a plurality of servers that perform a plurality of parallel services; transforming the non-linear QNM to a linear model by serializing the parallel services as sequential services; conducting a single-user test of the IT environment; based on the single-user test, measuring a plurality of hardware-based service demands related to a plurality of hardware resources, wherein a first hardware service demand is related to a web server, a second hardware service demand is related to an application server, and a third hardware service demand is related to a database server; inferring a plurality of software-based service demands on the linear model, wherein the plurality of software-based service demands are based on the plurality of hardware-based service demands, and wherein the inferring further comprises: estimating a first software demand that is related to a demand of executing a plurality of application server threads as being a sum of the second hardware service demand and the third hardware service demand; estimating a second software demand that is related to a demand of providing a plurality of database data sources as being equivalent to the third hardware service demand; and estimating a third software demand that is related to a demand of executing a web server connection by a web server as being a sum of the first hardware service demand, the second hardware service demand, and the third hardware service demand; receiving a system transaction rate based on the single-user user test of the IT environment; and calculating one or more predicted performance results of the IT environment based on the plurality of hardware-based service demands, the plurality of software-based service demands, and the system transaction rate.