Amblyomma americanum (L.) is a three-host tick that spends most of its life off-host and is an important vector of pathogens in the eastern United States. Our objectives were to develop a predictive statistical model that describes the number of active, off-host larvae from 2007 to 2011 and to determine the environmental variables associated with this pattern. Data used in this study came from monitoring conducted in northeast Missouri in which off-host ticks were collected from a permanent plot in a forest and an old field habitat every other week from approximately February to December. Variables examined were day length, degree days, total precipitation prior to sampling, wind speed, saturation deficit, number of adults prior to sampling, and collection site. Of the four regression models tested, the negative binomial model was selected. Fitted candidate models were compared relative to one another using values of eight model selection criteria and model averaging was used to develop a predictive model. The residual plots indicated that the weighted average model performs well in describing the number of larvae. Of the variables considered, the number of larvae was most strongly associated with increasing degree days, the number of active adults prior to sampling, and the forested site.