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A method based on electrical parameters and support vector regression for quantitative detection of somatic cell count (SCC) was exploded. Firstly, the SCC of 100 raw milk samples was confirmed by the standard microscope counting with iodine staining. And then, an interdigitated microelectrode was used in impedance measurements of milk samples in the frequency range from 0.01 Hz to 100 kHz. An equivalent electrical circuit of the milk samples was deduced for the measured impedance data. By using of Zview software, the electrical parameters of the equivalent electrical circuit were extracted and the relationships between these electrical parameters and the degree of mastitis were analyzed. At last, based on these electrical parameters and support vector regression (SVR), a quantitative detection model of SCC was established and its feasibility was studied. It was showed that one of the electrical parameters of RS was decreased with increasing of SCC, while other electrical parameters such as Cdl－T and Cdl－P presented a nonlinear trend. The SVR model was good for prediction of SCC with high precision except the negative samples. The average relative error was 29.40%, and the bovine mastitis detection rate for 1 (sub-clinical), 2 (relative serious infection), and 3 (serious infection) level of samples were 100%. 