This paper introduces a novel age estimation method using a new texture descriptor Weber Local Descriptor (WLD). This texture descriptor is analyzed in depth for age estimation problem. In the study, the multi-scale versions of holistic and spatial WLD (SWLD) descriptors are used to extract the age related features from normalized facial images. After finding a lower dimensional feature subspace, age estimation is performed using multiple linear regression. In addition a new approach of dividing image into regions for spatial texture extraction is proposed. Experiments on FG-NET, MORPH and PAL databases have shown that the proposed method gives better accuracy than the state of art age estimation approaches.