Accurate　analysis　of　electrochemical　properties,　along　with　a　profound　understanding　of　the　intrinsic　mecha-nisms　governing　variations　in　the　electrochemical　system,　holds　pivotal　significance　in　predicting　the　mechanical　performance　of　air-entrained　mortar.　This　study　employs　resistivity　and　electrochemical　impedance　spectroscopy　(EIS)　techniques　to　elucidate　the　electrochemical　attributes　of　air-entrained　mortar.　A　novel　equivalent　circuit　(EC)　model,　accounting　for　the　incorporation　of　bubbles,　is　developed　to　derive　electrochemical　parameters　for　air-entrained　mortar.　The　underlying　mechanisms　dictating　alterations　in　the　electrochemical　parameters　are　revealed　through　microscopic　characterization　techniques.　Additionally,　a　backpropagation　(BP)　neural　network　model　is　constructed　to　forecast　the　mechanical　performance　of　air-entrained　mortar.　The　results　demonstrate　that　air-entraining　admixtures　(AEA)-introduced　bubbles　exhibit　insulating　properties,　substantially　increasing　the　electrical　resistivity　(rho)　and　the　bulk　electrical　resistivity　(rho　bulk)　of　air-entrained　mortars.　The　developed　EC　model,　which　considers　the　air　effect,　aligns　well　with　the　test　results　in　Nyquist　plots.　The　insulating　properties　of　AEA-introduced　bubbles　is　attributed　to　the　formation　of　a　bubble　shell,　influenced　by　bubble　film　barriers　and　the　sulfonate-mediated　promotion　and　delay　of　Ca3Al2O6　and　Ca3SiO5　hydration.　The　BP　neural　network　model　showcases　exceptional　predictive　capabilities,　with　correlations　surpassing　0.96.　Consequently,　the　findings　of　this　study　can　be　applied　to　predict　the　mechanical　properties　of　air-entrained　mortar　in　practical　engineering　applications.