The order batching method improves the productivity of bucket brigade order picking systems (OPSs) by picking a group of small-sized orders as one batch in a single trip. The previous model batched orders by minimizing the completion time of batches. However, it is difficult to accurately calculate the completion time due to the complexity of the bucket brigade OPSs when considering non-identical pickers. Therefore, the previous model developed formulas to estimate the completion time. As a result, the errors in the estimated completion time lead to blocking occurring in the OPSs. To solve the blocking issue, we propose the Balanced Batching Model for Bucket Brigade (BBMB). Previous studies point out that bucket brigade OPSs achieve maximum productivity when the OPSs are in a balance status, and the balanced work content directly contributes to the OPSs’ balance. Based on these concepts, the BBMB model batches orders by balancing the work content in the OPSs. The BBMB model has increased the productivity of bucket brigade OPSs when handling a large number of small-sized orders. Compared to the previous model, the BBMB model reduces the blocking time percentage from 4.46-12.5% down to 0.26-5.66% in various scenarios designed for the simulation experiment.