Chrysanthemum, one of the economically most important and highly favored ornamental crops, exhibits a wide range of flower colors that are pivotal in determining its aesthetic value and market demand. However, probably due to the high genetic complexity of flower color traits, the progress in the dissection of genetic architecture and identification of quantitative trait nucleotides (QTNs) or candidate genes moves rather slowly. In this study, we systematically assessed the genetic variation of flower color phenotypes by integrating multiple color systems (RHSCC, CIELAB, and RGB) and four principal floral pigments (anthocyanins, chlorophylls, carotenoids, and flavonoids) in a diverse collection of 141 chrysanthemums. The results showed that the flower color traits exhibited a wide range of variations, with coefficients of variation (CV) varying from 26.00 % to 203.52 %. Among the 66 pairs of flower color traits, 48 exhibited highly significant correlations at p < 0.01 or p < 0.05 levels. Moreover, eight exponential regression models were established for predicting anthocyanin and carotenoid contents. Based on the 370,562 high-quality SNPs, genome-wide association studies (GWAS) revealed 36 QTNs significantly associated with flower color phenotype traits and 109 QTNs for pigment content traits. By integrating the functional annotation and expression profiles, a total of 809 candidate genes surrounding the QTNs were initially filtered out. The candidate genes encompassed multiple transcription factor families related to flavonoid metabolism pathways, including MYB, bHLH, WD40, NAC, and AP2/ERF transcription factors, as well as cytochrome P450-type enzyme genes. The current findings contribute to the accurate assessment of flower colors and provide valuable resources for the molecular breeding and functional analysis of flower color in chrysanthemums.