Livestock body weight (BW) and average daily weight gain (ADG) are primary indicators of beef cattle productivity. The conventional method of weighing involves moving the cattle to a weighing location, which is labor-intensive, stressful for the animals and has a negative impact on their growth. An alternative approach is to use special weighing platforms attached to the drinkers to weigh the animals. This method enables daily monitoring of BW and ADG without incurring additional labor costs or stress. In this study, an experimental weighing platform, previously developed at KazATU and named after S. Seifullin, was employed to measure livestock's partial body weight (PBW). The weighing platform recorded the weights of the animals on the front legs at one-second intervals, allowing for subsequent calculation of the animals' total weight. However, due to significant weight fluctuations observed when the animals were on the platform, the accuracy of calculating the weight based on a simple average of the one-second measurements was questionable. Hence, an algorithm was developed to determine live weight by analyzing the primary data from the scales and identifying moments of animal immobility during drinking. The calculated results were compared with both mean and median values and data from Kazakhstan's information base of selection and breeding work (IBSBW). The experimental method exhibited a stronger correlation (r = 0.925) with the actual IBSBW data compared to the mean method (r = 0.887) or the median method (r = 0.921).