Connectionist computational models have been extensively used in the study of reading: how children learn to read, skilled reading, and reading impairments (dyslexia). The models are computer programs that simulate detailed aspects of behaviour. This article provides an overview of connectionist models of reading, with an emphasis on the “triangle” framework. The term “connectionism” refers to a broad, varied set of ideas, loosely connected by an emphasis on the notion that complexity, at different grain sizes or scales ranging from neurons to overt behaviour, emerges from the aggregate behaviour of large networks of simple processing units. This article focuses on the parallel distributed processing variety developed by Rumelhart, McClelland, and Hinton (1986). First, it describes basic elements of connectionist models of reading: task orientation, distributed representations, learning, hidden units, and experience. The article then looks at how models are used to establish causal effects, along with quasiregularity and division of labor.