This paper presents a novel method for designing and optimizing electromechanical Σ∆ closed-loop for MEMS gyroscopes using multi-objective particle swarm optimization (MOPSO) algorithm. Initially, after designing an appropriate electrical Σ∆ modulator (Σ∆M) with desired performance, the equivalence between electrical Σ∆M and electromechanical Σ∆ closed-loop is exploited to calculate overall loop coefficients using approximations. Subsequently, the MOPSO algorithm, a multi-objective optimization algorithm based on Pareto dominance theory, is employed to optimize the subset of loop coefficients. This approach reduces simulation resources and time significantly while providing designers with a broader range of optimization choices. Using the proposed method, the designed fourth-order feedforward electromechanical Σ∆ closed-loop for MEMS gyroscopes achieves Signal-to-Noise and Distortion Ratio (SNDR) of 133.0 dB and reduces residual motion of the sense mode to a very low level of 9.07e-10 m, which outperforms other single-objective optimization algorithms. Simulation results demonstrate the robustness of the optimized electromechanical Σ∆ coefficients against gyroscope parameter variations within a range of ± 40%.