Cybernetic models rely on optimal control heuristics to predict the effects of metabolic regulation on the dynamics of biochemical reaction networks. Over the past 30+ years, this fertile paradigm has brought forth scores of research publications and has witnessed diverse applications ranging from bioprocess optimization and control to the redesign of cellular hosts through rational metabolic engineering. This review traces the historical development of the cybernetic modeling framework, beginning with its philosophical presuppositions and then following its progress from first-generation "lumped" cybernetic models to biochemically detailed second-generation models to recent "hybrid" cybernetic models that combine aspects of both first- and second-generation models. The broad and lasting influence of the cybernetic modeling approach is due in large part to the fact that it has remained true to its foundational principles while adapting over time to meet the changing demands of biotechnology research.