Blood meals by blacklegged ticks (Ixodes scapularis) on vertebrate hosts serve to transmit the agents of several zoonotic diseases, including Lyme disease, human babesiosis, and human granulocytic anaplasmosis, between host and tick. If ticks are aggregated on hosts, a small proportion of hosts may be responsible for most transmission events. Therefore, a key element in understanding and controlling the transmission of these pathogens is identifying the group(s) or individuals feeding a disproportionate number of ticks. Previous studies of tick burdens, however, have focused on differences in mean annual burdens between one or a few groups of hosts, ignoring both the strong seasonal dynamics of I. scapularis and their aggregation on hosts. We present a statistical modeling framework that predicts burdens on individual hosts throughout the year as a function of temporal-, site-, and individual-specific attributes, as well as the degree of aggregation in a negative binomial distribution. We then fit alternate versions of this model to an 11-year data set of I. scapularis burdens on white-footed mice (Peromyscus leucopus) and eastern chipmunks (Tamias striatus) to explore which factors are important to predicting tick burdens.