Recurrent artificial neural network has shown great success because of its interesting feature, each neuron in this type of artificial neural acts a computational element with memory, providing a neuron with ability to store the calculated output for the next stage of computation. In this paper we will introduce a methodology base on RNN features, this methodology will be used to build and run simulink based RNN models to solve linear programming problems, the introduced simulink models will be implemented in order to find the optimal values of LPM.