We present a simulation population model for the African tick Rhipicephalus appendiculatus, based on previous analyses of the mortality factors most closely correlated with observed population changes at 11 sites in equatorial and South Africa. The model incorporates temperature-dependent rates of egg production and development, climate-driven density-independent mortality rates, particularly during the adult-larval stage, and density-dependent regulation of both nymphs and adults. Diapause is also included for tick populations in southern Africa. The model successfully describes both the seasonality and annual range of variation in numbers of each tick stage observed at each of 4 test sites in Uganda, Burundi and South Africa. Sensitivity analysis showed that the final version of the model is robust to 4-fold variation in most parameter values (that were per force based on informed guesses), but is more sensitive to the regression coefficients determining density-dependent interstadial mortality (that were derived from analysis of field data). The model is able to predict the seasonality of ticks from a site in Kenya where a full prior population analysis was not possible because only adults and nymphs had been counted. The model is potentially applicable to other species of ticks, both tropical and temperate, to predict tick abundance and seasonality as risk factors for tick-borne diseases.