Technical Abstract: This article uses examples from recent research to evaluate select issues related to developing models that simulate phosphorus in the environment. Models are valuable because they force scientists to formalize understanding of P systems and identify knowledge gaps, and allow quantification of P transfer when monitoring is not possible. Model development should follow a procedure from a perceptual model of qualitative understanding to a conceptual model of equations to a procedural model of code. There are few implications for a flawed perceptual model when publishing scientific articles, but an inaccurate perceptual model stands little chance of predicting reliably. Because many different model structures are possible, it is possible for a model to be perceptually correct but conceptually incorrect. Translation of conceptual equations into procedural model code can also create model errors. Many P models share the same equations, many of which may be 30 years old and should be updated to reflect current science. Furthermore, models may be applied in situations for which their algorithms are inadequate. Models must be structured to allow for validation with field data or there is little confidence they can quantify P transfer. It can be a challenge to understand why a model does not validate and know when a model should be rejected. Model development and validation are often limited by data availability, but also by poor communication between field scientists and model developers. There may currently be too great an emphasis on data generation and too little emphasis on model development.