Abstract: OBJECTIVE To rapidly, correctly and nondestructively detect leaf moisture content by electrical measuring method in medicinal plants. METHODS The leaf capacitance, resistance and thickness were detected by using the self-designed parallel-plate capacitor and improving resistance measuring method in privet, polygonum multiflorum, ginkgo, kudzu and solanum sigrum sinne. Measured data was analyzed by SPSS 19.0 software for intraclass correlation coefficient verify the reliability of the data. The leaves were divided into training set and test set. The training set was analyzed with Excel regression. The fitting equation was established among leaf moisture content, capacitance, resistance and thickness. The fitting equation was used to predict the leaf moisture content in the test set. RESULTS The data reliability of capacitance among different leaves of the same medicinal plant was good. The data reliability of resistance among different leaves in polygonum multiflorum, kudzu and solanum sigrum sinne was good, and the data reliability of leaf resistance was general in privet and Ginkgo. The data reliability of capacitance and resistance among different medicinal plants was general. The data reliability of thickness among groups of different medicinal plants was good. By Excel regression analysis, R² was 0.959 7, adjusted R² was 0.951 0, significant value P=5.36×10^-10, fitting equation Y=23.548 3+0.021 6 X₁+12.705 8 X₂+106.786 1 X₃, DW=2.284, the fitting effect of the model was good. The model was used to predict the moisture content of the test set, and the errors were between 1.98% and -1.55% compared with the drying method. CONCLUSION The model can be used as a generic model for predicting leaf water content of the five medicinal plants.