To determine the appropriate number of DNA pooled samples and reliable association algorithms for bulked segregant analysis (BSA) in pepper, this study used F₂ segregating populations constructed from inbred lines with light-yellow (CSJ009) and green (CSJ010) immature fruit color. 30 (from a population of 220 F₂ individuals in 2019) and 50 (from a population of 788 F₂ individuals in 2021) extreme phenotype individuals were selected to construct DNA bulks, respectively, for whole-genome resequencing (WGRS) and BSA analysis. The mapping effects of SNP-index and ED algorithms were compared. The results showed that the sequencing depth of the 50-sample pool (average 50.92×) was higher than that of the 30-sample pool (above 35×), and the Q₃₀ quality value was better (above 94.71%). The error rates of SNP and InDel marker detection were lower, but the mapping results were more complex. The SNP-index algorithm detected 235 peak regions (126 of which were negative peak regions) at the 99% confidence level in the 50-sample pool, making it difficult to lock onto the core candidate regions, while the 30-sample pool only detected 21 peak regions, mainly concentrated on chromosome 9. The ED algorithm detected 22 peak regions (all on chromosome 9) at the 99% confidence level in the 50-sample pool, and 13 peak regions (concentrated in the 29.5 Mbp interval on chromosome 9) in the 30-sample pool. Combined with the results of genetic linkage analysis verification, the SNP-index algorithm was more reliable than the ED algorithm. In conclusion, in the BSA mapping of pepper fruit color genes, the effect of constructing pools with 30 extreme phenotype plants is better than that with 50, and the SNP-index algorithm is more suitable for the initial mapping of target genes. The results provide a scientific reference for the experimental design of BSA gene mapping in pepper and similar crops.