Sensitive MEMS-based thermal flow sensors are the best choice for monitoring the patient’s respiration prompt diagnosis of breath disturbances. In this paper, open space micro-calorimetric flow sensors are investigated as precise monitoring tools. The differential energy balance equation, including convection and conduction terms, is derived for thermal analysis of the considered sensor. The temperature-dependent thermal conductivity of the thin silicon-oxide membrane layer is considered in the energy balance equation. The derived thermal non-linear differential equation is solved using a well-known analytical method, and a finite-element numerical solution is used for the confirmation. Results show that the presented analytical model offers a precise tool for evaluating these sensors. The effects of flow and thin membrane film parameters on thermo-resistive micro-calorimetric flow sensors’ performance and sensitivity are evaluated. The optimization has been performed at different flow velocities using a genetic algorithm method to determine the optimum configuration of the considered flow sensor. The geometrical parameters are selected as a decision variable in the optimization procedure. In the final step, using optimization results and curve-fitting, the expressions for the optimum decision variables have been derived. The sensor’s optimum configuration is achieved analytically based on flow velocity with the analytical terms for optimum decision variables.