Although single-cell intrinsic structural and electrical parameters (e.g., Dc of cell diameter, Dn of nuclear diameter, σcy of cytoplasmic conductivity and Csm of specific membrane capacitance) are promising for cell-type classification, they cannot be obtained simultaneously due to structural limitations of previously reported flow cytometry. This paper presented a microfluidic flow cytometry made of a double T-type constriction channel plus a predefined fluorescence detection domain, capable of high-throughput characterizing single-cell Dc, Dn, σcy and Csm leveraging a home-developed impedance-fluorescence model. As a demonstration, the microfluidic platform quantified Dc, Dn, σcy and Csm from ~10,000 individual cells of three well-established tumor cell lines of A549, SW620 and HeLa where successful rates of cell-type classification were estimated as 54.5% ± 1.3% (Dc), 68.9% ± 6.8% (Dc + Dn) and 84.8% ± 4.4% (Dc, Dn, σcy + Csm) based on neural pattern recognition. Then Dc, Dn, σcy and Csm derived from ~10,000 single cells of K562 vs. Jurkat of leukemia and SACC-LM vs. CAL 27 of oral tumor were quantified and compared, where successful rates of cell-type classification were estimated as 87.3% (K562 vs. Jurkat) and 79.5% (SACC-LM vs. CAL 27), respectively. In summary, the microfluidic platform reported in this study could quantify single-cell intrinsic structural and electrical parameters simultaneously, leading to significant increases in successful rates of cell-type classification.