We discuss how the topological notions of unimodal category and persistence can be applied to the foundational statistical problem of estimating the probability density of a one-dimensional random variable from sample data. The resulting technique outperforms conventional methods on multimodal data, and can also indicate when a conventional method is likely to offer better performance. Prospects for applications to multidimensional problems will also be discussed.