Lindenmayer systems (L systems) provide a concise mathematical formulation for creating simulations of plants that are descriptively accurate, while also taking into account various molecular-level controls. At present, most plant models are created manually by experts from measured data and scientific knowledge. However, manual creation does not scale to the creation of thousands of models needed to correspond to plants developed by plant breeders. In this talk, we discuss existing and new approaches to the automatic inference of Lindenmayer systems from data, with a focus on inductive inference. This includes exact approaches, approaches using evolutionary algorithms, and other heuristics.