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The police service dog has a long history stretching as far back as the 1400's. One of the most popular dog breeds deployed by both the police and military has been the German Shepherd yet little is known about the morphology or body segment parameters of this breed. Knowledge of these measures is essential for developing biomechanical models that can guide clinicians in developing surgical interventions, injury treatment and prevention procedures. The aim of this thesis was to provide a complete set of body segment parameters and inertial properties for the German Shepherd. In addition, a canine motion capture suit and marker model was proposed for use with this dog population. Morphometric measures and 3-dimensional inertial properties, including mass, centre of mass, moment of inertia and volume, were measured from 17 segments from each of 6 German Shepherd police service dog cadavers. Measurements were performed with frozen segments similar to the procedure on primates described by Reynolds (1974), on humans by Chandler et al. (1975) and on horses by Buchner et al. (1997). Using whole body mass and geometric modelling, multiple linear regression equations were developed from the collected data so that they may be used to estimate segment masses and inertial tensors in living dogs. Using a custom Lycra suit and 44-marker full-body marker set, kinematic data were collected to assess the practicality of the model, to observe the dogs' acceptance of the motion capture suit and to ensure fore and hind limb flexion/extension angles were comparable to those of other canine studies. Using frozen cadavers, tissue loss was minimal at an average loss of 0.49% of total body mass. Hind limbs, at 6.8% of body mass, were 2.3% heavier than the forelimbs. Of the over 100 morphometric measures analysed, 33 were kept for inclusion in the linear regression equations and joint centre estimations. Analyses of body mass alone, found that, except for the abdominal segment (r = .845, p≤.05), body mass did not correlate well with segmental masses. Similarly for moments of inertia, only the manus and pes produced predictive results using body mass alone. 11 regression equations were developed for predicting segment masses, and 33 equations were developed for predicting moments of inertia about the three primary axes of each segment. Regression correlation analyses were summarized for each segment and a table of normalised average segment masses, centres of mass, radii of gyration and segment densities was produced. Five police service dogs took part in the evaluation of the motion capture suit. Overall the marker set and suit performed well and was well-received by dog/handler teams. The markers took very little time to apply, remained in place for the majority of trials and the suit itself did not visibly affect the dog's natural movement. An analysis of the kinematic data produced outputs showing characteristic patterns of flexion/extension similar to those found in other canine research. With the development of regression equations for predicting segment mass and moments of inertia combined with the proposed marker model and novel method of marker attachment, inverse dynamic analyses may be applied in future investigations of canine mechanics, potentially guiding surgical procedures, rehabilitation and training for the German Shepherd breed. Key Words: Canine, German Shepherd, morphometry, kinematics, kinetics, inertial properties, body segment parameter, segment model, moment of inertia, mass distribution.