Intralimb proportions provide insights into growth, development, populations history, and adaptation across human groups. However, the conventional approach of calculating brachial and crural indices for individual skeletons and comparing assemblages using sample means is not feasible in commingled remains. This study aims to assess the reliability of an “aggregate method” based on the ratio of sample means of limb bone lengths as an alternative to conventionally calculated indices. We examined the correlation between the aggregate and conventional indices using data from ≥124 worldwide groups (≥2000 adults). The impact of sample size, commingling degree, and within‐group variation on the correspondence between conventional and aggregate indices was further evaluated using simulated datasets. Reliability was measured using the absolute differences between the aggregate and “true” population mean indices and the proportion of simulations producing large errors (>0.02, the average within‐group variation among observed populations). Strong correlations are observed between the aggregate and conventional indices across groups in the empirical dataset. Simulation analyses indicates that larger samples improve prediction reliability, while increased commingling and within‐group variation reduce accuracy. The aggregate method is robust when upper limb samples contain >30 bones (lower limb >50), with more than half of the bones representing proximal and distal elements from the same individuals, and the standard deviation in the index is smaller than 0.02. With sufficient sample sizes, the “aggregate method” is a reliable alternative for estimating average intralimb proportions in commingled and poorly preserved skeletal assemblages, enhancing the research potential of such collections.
