In this book, a stochastic transformation method is proposed that reduces (by using sample path arguments) a certain set of performance evaluation problems to those that are described by the so-called first-order multi-regime feedback Markov fluid queues (FMFFQ). In addition, we provide differential equations and boundary conditions for the solvability of such fluid queues and we propose computationally efficient and stable numerical algorithms to find their steady-state performance measures. We apply this method to a number of scenarios, the queueing analysis of which are already available in the literature, with the goal of demonstrating the generality of this approach. The real value we add is to use this method to solve exactly the queueing systems for which exact analytical methods were not available and we present three such problems.