A hyperspectral technology was utilized to estimate the Equivalent Water Thickness (EWT) of apple leaves in a rapid and nondestructive way, which could provide a reference for the early warning of growth and drought of apple trees. Taking the leaves of Red Fuji apple trees in Qixia, Yantai, Shandong Province as experimental materials, the correlation among EWT, original spectral reflectance and 13 kinds of transformation spectral reflectance was analyzed on the basis of the spectral reflectance of apple tree leaves and the calculation of their EWT. After the sensitive wavelengths were screened out, an estimation model of the EWT of apple tree leaves based on support vector regression was established. Among the 13 kinds of spectral transformation, 3 kinds of transformation such as the first derivative (FDR), the first derivative of the square root (FD(SqrtR)) and the first derivative of the logarithm of the reciprocal (FD[Lg(1/R)]) had better correlation. The sensitive wavelengths for estimating the EWT of apple tree leaves were determined. On the basis of the support vector regression, a mode for quantitatively estimating the blade EWT was established. The coefficient of determination R2 of the validation set reached 0.8147 and the relative percent deviation (RPD) reached 2.2671. The results showed that the model had better estimation ability and the support vector regression was more suitable to estimate the EWT of apple tree leaves. This method provided technical support for the quantitative estimation of the growth status of apples by hyperspectral techniques.