Background: The seasonal variation in circulating 25-hydroxyvitamin D [25(OH)D] concentrations is large relative to mean values. Single measurements may misclassify annual exposure, which may lead to bias in research and complicate clinical decision making. Objective: We aimed to develop and validate a model for adjusting a single measurement of a serum 25(OH)D concentration to the time of year it was measured. Design: We measured serum 25(OH)D concentrations by using mass spectrometry in 6476 participants from the Multi-Ethnic Study of Atherosclerosis at baseline and again in a subset of 368 participants at a median of 17 mo later. We estimated a cosinor model to describe the seasonal variability in 25(OH)D concentrations and evaluated this model by using follow-up 25(OH)D measurements. Results: The mean age of subjects was 62.1 y, 61.2% of participants were nonwhite, and 53.3% of participants were women. The cosinor model predicted follow-up 25(OH)D concentrations better than a single measurement [difference in root mean squared error (RMSE): 1.3 ng/mL; P< 0.001]. The cosinor model also better predicted the measured annual mean 25(OH)D concentration (difference in RMSE: 1.0 ng/mL; P< 0.001). Annual mean 25(OH)D concentrations estimated from the cosinor model reclassified 7.1% of participants with regard to 25(OH)D deficiency, which was defined as <20 ng/mL. An estimated annual mean 25(OH)D concentration <20 ng/mL was significantly associated with lower bone mineral density, whereas an untransformed 25(OH)D concentration <20 ng/mL was not. Conclusions: Cross-sectional data can be used to estimate subject-specific mean annual 25(OH)D concentrations from single values by using a cosinor model. The tool we developed by using this approach may assist research and clinical care of adults in North America by reducing the misclassification of 25(OH)D deficiency.