【Objective】 To build models for estimating chlorophyll a and chlorophyll b contents in potato，Solanum tuberosum， leaves by using hyperspectral vegetation indices, and provide a basis for scientific and nondestructive estimation of chlorophyll content in potato leaves. 【Method】Leaf spectral reflectance was measured for potato plants at different growth stages under different nitrogen levels by using a portable spectrometer. The hyperspectral vegetation indices were extracted from leaf spectral reflectance. The contents of chlorophyll a and chlorophyll b in potato leaves were measured, and the relationship between hyperspectral vegetation index and chlorophyll content was analyzed. 【Result】There were 12 vegetation indices with relatively good correlations with chlorophyll content. Modified normalized difference index(mND₇₀₅), modified simple ratio index(mSR₇₀₅),MERIS terrestrial chlorophyll index(MTCI) and modified chlorophyll absorption reflectance index(MCARI) had the highest correlations with chlorophyll contents among the 12 vegetation indices. Estimation models were established based on above-mentioned four indices. The power model based on MTCI offered the best estimation of chlorophyll a content, and the index model based on MCARI offered the best estimation of chlorophyll b content.【Conclusion】The power model based on MTCI and the index model based on mND₇₀₅ can be respectively used to estimate chlorophyll a and chlorophyll b contents in potato leaves with relatively high accuracy，and indirectly monitor nitrogen deficiency in potato plants.