This paper describes a prototype system for surgical planning and prediction of human facial shape after craniofacial and maxillofacial surgery for patients with facial deformities. For this purpose it combines, unifies, and extends various methods from geometric modeling, finite element analysis, and image processing to render highly realistic 3D images of the post surgical situation. The basic concept of the system is to join advanced geometric modeling and animation systems such as Alias with a special purpose finite element model of the human face developed under AVS. In contrast to existing facial models we acquire facial surface and soft tissue data both from photogrammetric and CT scans of the individual. After initial data preprocessing, reconstruction, and registration, a finite element model of the facial surface and soft tissue is provided which is based on triangular finite elements. Stiffness parameters of the soft tissue are computed using segmentations of the underlying CT data. All interactive procedures such as bone and soft tissue repositioning are performed under the guidance of the modeling system which feeds the processed geometry into the FEM solver. The resulting shape is generated from minimizing the global energy of the surface under the presence of external forces. Photorealistic pictures are obtained from rendering the facial surface with the advanced animation system on which this prototype is built. Although we do not claim any of the presented algorithms themselves to be new, the synthesis of several methods offers a new facial model quality. Our concept is a significant extension to existing ones and, due to its versatility, can be employed in different applications such as facial animation, facial reconstruction, or the simulation of aging. We illustrate features of our system with some examples from the Visible Human Data Set.TM CR Descriptors: I.3.5 [Computational Geometry and Object Modeling]: Physically Based Modeling; I.3.7 [Three-Dimensional Graphics and Realism]; I.4.6 [Segmentation]: Edge and Feature Detection Pixel Classification; I.6.3 [Applications]; Additional