This chapter offers ideas on how classification can capture more evolutionary information, be done quantitatively, and yield more predictive systems. The sole reliance on cladistic branching patterns as a framework for hierarchical classification can be misleading. The challenge is basically how to quantitatively integrate divergence, the patristic dimension of phylogeny, with cladistic data. A number of alternatives have been published over the past 35 years, and this chapter highlights some of them. Emphasis is placed on using distinctness among and cohesion within groups based on evolutionarily significant characters and states.