Body condition score (BCS) is a method that is commonly used in the diagnosis of nutritional status in small animals. BCS has been recognized as one of the screen methods of nutrition diagnosis by the American Animal Hospital Association in 2010. However, this method is subjective due to its sensory evaluation. Therefore, we built a BCS model for the BCS diagnosis and examined its accuracy. Twenty-four dogs with varied BCS were used for this examination. The BCS model has been made by stacking rubber sheets having different thickness on the rib which was artificially made by resin. BCS diagnosis was performed by 120 students in the Department of Animal Nursing. They were divided into two groups and one group diagnosed without the BCS model and another group used the BCS model. At the same time, body fat was measured by using a body fat analyzer for dogs (Kao Healthlab BIF-10). Variability in the data was greater in the group that was not using the BCS model, while the variability in the data of group using the BCS model was small. Statistically significant differences were observed between the two groups. These results suggest the accuracy of the BCS diagnosis increases using the BCS model in the clinical practice. Also this BCS model is useful for the training of BCS diagnosis to veterinary medical personnel.