The utilization of Municipal Solid Waste (MSW) fines in ground improvement and road construction has gained special attention due to its environmental and economic benefits. In the present study, the Artificial Neural Networks (ANN) technique has been used for modeling the monotonic/static strength behaviour of MSW fines reinforced with waste fibers. The laboratory investigation has been carried out to understand the strength behaviour of MSW fines reinforced with waste fibers under static undrained loading conditions. After analysing the laboratory results, a deep learning models has been used to improve the learning efficiency of the artificial neural network (ANN) and to simulate the static strength behaviour of MSW fines reinforced with fibers. The results indicate that this innovative ANN technique and deep learning approach effectively simulate the undrained shear strength response of the MSW fines, significantly when it is strengthened with fiber reinforcement during an undrained triaxial loading condition.