Background Relatively little is known about the stability of a diagnosis of episodic migraine (EM) or chronic migraine (CM) over time. This study examines natural fluctuations in self-reported headache frequency as well as the stability and variation in migraine type among individuals meeting criteria for EM and CM at baseline. Methods The Chronic Migraine Epidemiology and Outcomes (CaMEO) Study was a longitudinal survey of US adults with EM and CM identified by a web-questionnaire. A validated questionnaire was used to classify respondents with EM (<15 headache days/month) or CM (≥15 headache days/month) every three months for a total of five assessments. We described longitudinal persistence of baseline EM and CM classifications. In addition, we modelled longitudinal variation in headache day frequency per month using negative binomial repeated measures regression models (NBRMR). Results Among the 5464 respondents with EM at baseline providing four or five waves of data, 5048 (92.4%) had EM in all waves and 416 (7.6%) had CM in at least one wave. Among 526 respondents with CM at baseline providing four or five waves of data, 140 (26.6%) had CM in every wave and 386 (73.4%) had EM for at least one wave. Individual plots revealed striking within-person variations in headache days per month. The NBRMR model revealed that the rate of headache days increased across waves of observation 19% more per wave for CM compared to EM (rate ratio RR, 1.19; 95% CI, 1.13–1.26). After adjustment for covariates, the relative difference changed to a 26% increase per wave (RR, 1.26; 95% CI, 1.2–1.33). Conclusions Follow-up at three-month intervals reveals a high level of short-term variability in headache days per month. As a consequence, many individuals cross the CM diagnostic boundary of ≥15 headache days per month.Nearly three quarters of persons with CM at baseline drop below this diagnostic boundary at least once over the course of a year. These findings are of interest in the consideration of headache classification and diagnosis, the design and interpretation of epidemiologic and clinical studies, and clinical management.