Epigenetic mechanisms control gene expression in a way that is stably propagated over multiple cell divisions, but which is also flexible enough to respond to environmental influences. This intermediate position between stability and plasticity renders epigenetic information highly useful for monitoring cellular states in the context of personalized medicine. Epigenetic alterations have also been identified as causal events for common diseases such as cancer and autoimmune disorders. The goal of epigenetic biomarker development is to design experimental assays that produce relevant information for diagnosis, prognosis and therapy optimization in routine clinical treatment and drug discovery. Here, I outline a systematic approach to epigenetic biomarker development and highlight key bioinformatic tools that facilitate discovery, optimization and validation of novel biomarkers.