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In spite of numerous programs and interventions, homelessness remains a significant societal concern. Long-term homelessness is particularly problematic because it can be increasingly difficult to escape from, and because it represents a continuous drain on societal resources. This paper develops a model for predicting long-term homelessness in response to a simple question: if an individual becomes homeless, what influences the individual's slide to long-term homelessness? The data we analyze to answer the question comes from the City of Boston. The model points to race, veteran status, disability, and age as key factors that predict this slide. The paper describes and illustrates the model along with problems encountered in data preparation and cleansing, prior scholarly work that helped to shape our decisions, and collaboration with participants in the ecosystem for homeless care that complemented the model-building effort. The results are important because they point to possible policy interventions (programs and funding) and process improvements (at homeless shelters) to mitigate this slide.