In 1983, Broadbent introduced the basic technique of cephalometric radiography or """"""""cephalometrics"""""""" for the purpose of making head and face measurements on living and growing individuals. Since its introduction, cephalometrics has grown to be an integral tool for the researchers and clinicians in describing and quantifying craniofacial morphology and dysmorphology. Few investigators have applied multivariate statistical analysis to the cephalometric measurements for the identification, interpretation and classification of craniofacial anomalies. My main analytic technique will be to employ multivariate statistics as a primary tool to study patterns of craniofacial variation in individuals with dysmorphic syndromes. The research objectives are: (1) To establish the range and limits of normal craniofacial variation for diagnostically significant cephalometric parameters. (2) To assess age and sex-specific changes in the normal cephalometric parameters so that they could be used not only to interpret the normal craniofacial parameters for specific age and sex, but also for the assessment of abnormal parameters in dysmorphic syndromes. (3) To investigate constrasting patterns of variation between the normal and dysmorphic syndromes by discriminant function analysis. This analysis delineates the most discriminating parameters between the groups and can identify discriminant functions useful in correctly diagnosing the specific syndromes. Most importantly, those gene carriers with uncertain clinical diagnosis who remain undiagnosed, but are at risk to develop the disease later in life, can be identified for early initiation of the need care. (4) To delineate basic patterns of craniofacial variation by factor (component) analysis. This type of analysis will identify craniofacial factors which are more meaningful anatomically and genetically. The variables selected from the factors will ultimately be employed in an attempt to construct a craniofacial pattern profile to be used as a diagnostic aid. The ultimate aim of this study is to devise simple procedures for cephalometrically identifying and classifying craniofacial anomalies.