Serodiagnosis of arthropod-borne viruses (arboviruses) at the Division of Vector-Borne Diseases, CDC, employs a combination of individual enzyme-linked immunosorbent assays and microsphere immunoassays (MIAs) to test for IgM and IgG, followed by confirmatory plaque-reduction neutralization tests. Based upon the geographic origin of a sample, it may be tested concurrently for multiple arboviruses, which can be a cumbersome task. The advent of multiplexing represents an opportunity to streamline these types of assays; however, because serologic cross-reactivity of the arboviral antigens often confounds results, it is of interest to employ data analysis methods that address this issue. Here, we constructed 13-virus multiplexed IgM and IgG MIAs that included internal and external controls, based upon the Luminex platform. Results from samples tested using these methods were analyzed using 8 different statistical schemes to identify the best way to classify the data. Geographic batteries were also devised to serve as a more practical diagnostic format, and further samples were tested using the abbreviated multiplexes. Comparative error rates for the classification schemes identified a specific boosting method based on logistic regression "Logitboost" as the classification method of choice. When the data from all samples tested were combined into one set, error rates from the multiplex IgM and IgG MIAs were <5% for all geographic batteries. This work represents both the most comprehensive, validated multiplexing method for arboviruses to date, and also the most systematic attempt to determine the most useful classification method for use with these types of serologic tests.