A complicated issue in many cell signaling pathways is mainly related to the number of state variables and parameters. This is computationally very expensive, it may sometimes difficult to predict their model dynamics. Such problems in cell signaling pathways can be simplified and analyzed easily based on model reduction approaches. In this work, we suggest a model reduction technique based on entropy production analysis and lumping of isolated species. The proposed approach provides an improvement in the field of cell signaling pathways. We apply this technique to minimize the number of reactions and elements for the elongation factors EF–Tu and EF–Ts pathways. Computational simulations are computed for the given initial values and parameters. The results provide accuracy and important agreement between the original and reduced models. More interestingly, the model approaches here may apply to a variety of complex cell signaling networks and may use for theoretical and practical purposes.