This paper addresses the optimization design problem of electromagnetic conductivity sensors for low conductivity measurements. The working principle of electromagnetic conductivity sensors is analyzed, and a physical model is constructed. The influence of excitation signal parameters, magnetic core dimensions, core spacing, excitation coil turns, and receiver coil turns on the output voltage is considered. An improved model for electromagnetic conductivity measurement is proposed, taking into account the multiplicity of excitation frequencies. Specifically, the excitation frequency directly affects the output voltage and also modifies the magnetic permeability of the core through the magnetostrictive effect, thereby influencing the output voltage. Theoretical analyses of the main parameters, such as frequency, spacing, and turns, are conducted using a comparative approach with experimental results. It is found that it exists an optimal frequency range where the output voltage remains relatively stable despite fluctuations in frequency. By adjusting the spacing between the two magnetic cores, coupling voltage between them is reduced, resulting in a higher proportion of effective signals and improved accuracy. The accuracy of the theoretical model is verified through experimental validation. Furthermore, the optimized parameters are employed in the design of a conductivity probe, which is calibrated using conductivity standard solutions. Comparative experiments are conducted with a German-made conductivity meter from Bode to calculate the Pearson correlation coefficient, demonstrating the accuracy and high reliability of the optimized model.