Modified hypercubes (MHs)  have been proposed as the building blocks of hypercube-based parallel systems that support incremental growth techniques. In contrast, systems comprising the standard hypercube can not be expanded in practice. Processor allocation for MHs is a more difficult task due to a slight deviation in their topology from that of the hypercube. This paper addresses the processor allocation problem for MHs and proposes two strategies which are based, partially or entirely, on a table look-up approach. The proposed strategies are characterized by a perfect subcube recognition ability and a superior performance. Further, two existing processor allocation strategies for pure hypercubes, namely the buddy and free list strategies, are shown to be ineffective for MHs, in the light of their inability to recognize many available subcubes.