Purpose of the Review Exposure to essential and non-essential metals is widespread. Metals exposure is linked to epigenetic, particularly DNA methylation, differences. The strength of evidence with respect to the metal exposure type, timing, and level, as well as the DNA methylation association magnitude, and reproducibility are not clear. Focusing on the most recent 3 years, we reviewed the human epidemiologic evidence (n = 26 studies) and the toxicologic animal model evidence (n = 18 studies) for associations between metals exposure and DNA methylation. Recent Findings In humans, the greatest number of studies focused on lead exposure, followed by studies examining cadmium and arsenic. Approximately half of studies considered metals exposure during the in utero period and measured DNA methylation with the genome-wide Illumina arrays in newborn blood or placenta. Few studies performed formal replication testing or meta-analyses. Toxicology studies of metals and epigenetics had diversity in model systems (mice, rats, drosophila, tilapia, and zebrafish were represented), high heterogeneity of tissues used for DNA methylation measure (liver, testis, ovary, heart, blood, brain, muscle, lung, kidney, whole embryo), and a variety of technologies used for DNA methylation assessment (global, gene specific, genome-wide). The most common metals tested in toxicologic studies were lead and cadmium. Together, the recent studies reviewed provide the strongest evidence for DNA methylation signatures with prenatal metals exposures. There is also mounting epidemiologic evidence supporting lead, arsenic, and cadmium exposures with DNA methylation signatures in adults. The field of metals and DNA methylation is strengthened by the inclusion of both epidemiology and toxicology approaches, and further advancements can be made by coordinating efforts or integrating analyses across studies. Future advances in understanding the molecular basis of sequence specific epigenetic responses to metals exposures, methods for handling exposure mixtures in a genome-wide analytic framework, and pipelines to facilitate collaborative testing will continue to advance the field.