Marker-assisted backcrossing is a powerful method for developing new cultivars. To develop genomic-wide markers, genotyping-by-sequencing (GBS) can be an efficient method. However, unrefined low-quality markers and missing data between markers can contribute to hampering the marker selection process, particularly in multi-way crosses. In this study, we aimed to calculate the recovery rate of offspring individuals and minimize errors that occur among a large number of markers. Initially, missing data were imputed by comparing samples using the k-nearest neighbor (k-NN) algorithm. Thereafter, low-quality single-nucleotide polymorphisms (SNPs) were corrected by applying the graphical representation method based on the k-NN algorithm in order of the SNPs in a chromosome designed for a multi-parental population. Four-way cross and double-backcrossed tomato BC₁F₁ (230 lines) and BC₂F₁ (96 lines) populations were genotyped by GBS. The genotype of samples of the BC₁F₁ and BC₂F₁ populations was determined based on the parental haplotype. Thus, the method of visualizing the genotype of offspring individuals, generated via crosses of multiple parents, not only improves estimation of the recovery rate but also facilitates easier selection in breeding programs.