Body Condition Score (BCS) is an important index for assessing body fat accumulation in cattle and plays a crucial role in managing cattle productivity, feeding efficiency, and overall health. Currently, BCS evaluations predominantly rely on visual assessment and palpation by specialized personnel, which is time-consuming and labour-intensive. Consequently, many farms refrain from utilizing BCS for cattle management. Previous studies have focused on BCS evaluation of stationary dairy cows in rotary parlours, but this approach is not feasible for small and medium-sized livestock producers lacking such facilities. To enable BCS management for dairy cows on any farm, we propose a system utilizing image processing technology for evaluating cows while walking. In this study, we capture images using three 3D cameras and construct an estimation model using feature extraction and multiple regression analysis. This model allowed the evaluation of cows with large BCS within an error margin of 0.25. Our findings suggest that this approach can significantly streamline BCS evaluation, making it accessible and practical for a broader range of dairy farms.