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In the past, different groups had used various types of nomenclature to classify children with persistent arthritis including “juvenile rheumatoid arthritis” (American College of Rheumatology [ACR]) and “juvenile chronic arthritis” (European League Against Rheumatism), which created problems in comparing research studies and outcomes. The goal of the International League of Associations for Rheumatology (ILAR) is to identify subtypes of JIA for research purposes that are homogeneous and mutually exclusive. JIA classification is currently based on predominant clinical and laboratory features and the number of involved joints at disease onset. There is a continual renewal process, with the second revision occurring in Edmonton in 2001, which is presented in Table 107-1. However, classification systems are ever evolving, and categorization may evolve to more biologically and genetically similar subgrouping, especially with recent advances in etiology and pathogenesis. For example, age of onset may be a more biologically relevant parameter to distinguish between subtypes of JIA than classification based on number of involved joints. PBMC gene expression analysis reveals biologic differences between patients with early-onset ( 6 years) JIA, which was independent of oligoarthritis or polyarthritis subtype. Ravelli and colleagues provided clinical support for this approach, showing that antinuclear antibody (ANA)-positive patients with oligoarthritis and rheumatoid factor (RF)-negative polyarthritis were similar in terms of early age at onset, female predilection, increased frequency of asymmetric arthritis, and increased frequency of uveitis. Pattern recognition is perhaps the most significant skill needed by clinicians in the diagnostic evaluation of patients. The usual patterns in children with rheumatic diseases often overlap with malignancies, infection, and trauma (especially nonaccidental). Therefore it is crucial to evaluate these diagnostic possibilities first before accepting the diagnosis of JIA. The ILAR categories are meant to simplify classification and are useful for typical presentations of KEY POINTS