Facial expression synthesis is a process of generating new face shapes from a given face and still retain the distinct facial characteristics of the initial face. The generated facial expressions can be used to improve the performance of existing face identification systems, or to enhance human recognition. Earlier work on synthesizing face shapes used 2D face images. Only recently, the work moved to using 3D face shapes given the availability and improvement in 3D scanner technologies. The advantage of 3D faces over 2D image data is that 3D face holds more geometric shape data and is invariant to poses and illumination. This paper aims to give an overview of the methods used for 3D facial expression synthesis. We present an overview of 3D face expression synthesis, its applications and benefits and then we review some of the most resent 3D face expression synthesis approaches.