his paper provides a new toot for those concerned with the design or performance of packed distillation columns. It gives a simple method to assess the sensitivity of a packed bed to maldistribution. Despite extensive prior work on this topic, the concept proposed here appears to have been previously overlooked. A parallel column model is often used to assess the sensitivity of a packed bed in a distillation column to liquid or vapour maldistribution. However, it is well known that the parallel column model is oversimplified because it involves an arbitrary number of parallel columns, it neglects lateral mixing, and the actual extent of maldistribution is unknown. For these reasons, the parallel column model can only be used as a way of identifying packed beds that are particularly susceptible to maldistribution, rather than as a predictive design tool. In this paper it is shown that sensitivity to maldistribution can be predicted much more simply using a single parameter f(max), which is the maximum maldistribution that could possibly occur in a parallel column while still being able to achieve the required separation. It is shown that f(max) can be determined very simply, for example from the output of a conventional column simulation program, and a parallel column model is not actually needed. Using f(max), the sensitivity to maldistribution of a proposed packed bed can now easily be compared at the design stage to other packed beds that are known to work satisfactorily. If necessary, the design can then be modified to reduce the sensitivity to maldistribution. Routine calculation of f(max), during design will help to reduce the significant number of distillation column problems that presently occur because of mal distribution.