Peristaltic conveyance can be used for the sorting and transport of delicate and nonrigid objects such as meat or soft fruit. The non‐linearity and stochastic behavior of peristaltic systems make them difficult to control. Optimizing controllers using machine learning represents a promising path to effective peristaltic control but currently, there is no suitable simulated model of a peristaltic table in which to run these optimizations. A simple, simulated model of a peristaltic conveyor that can be used for optimizing peristaltic control on a variety of peristaltic tables is presented. This simulator is demonstrated through a limited control problem evaluated on our real‐world system that is built for peristaltic conveyance. This simulator is available as the python package PeriSim so that it can be used by the robotics community for peristaltic control development.