The level of aggregation of reported data has limited the proper accounting of live animals in most, if not all, livestock models, making the consistency of their underlying biologics suspect. We develop an econometric methodology to decompose a wide range of aggregate data. This method is applied to estimate a disaggregated average cattle slaughter weight for calves, cows, and other cattle from total beef production data in the European Union. The estimated model gave acceptable statistical properties and estimated slaughter weights that closely correspond to reported sample-based slaughter weights across all cattle categories. The model has a good fit, no serial correlation, and highly significant coefficients with consistent signs. Standard validation statistics suggest that the model is able to track well both the mean and variability of the actual average cattle slaughter weight. Furthermore, other decompositions using the same methodology were successful in other countries–New Zealand, and Mexico; other sectors–sheep; and other aggregate data–dairy and beef calving rates.