With the advancement of genetic studies and the technology applied to the genotyping of molecular markers, the identification of polymorphisms associated with the characteristics of economic interest became more accessible, allowing its use to increase the accuracy of prediction models of the genetic merit of the animals. This advance also made it possible to increase the accuracy of studies to identify QTLs for characteristics of economic interest. However, the commonly used markers for this purpose are SNPs, which because they are bi-allelic may not be very efficient in identifying QTLs. The haplotypes, multi-allelic, are more likely to be in linkage disequilibrium (LD) with QTLs. Thus, the objective of this work was to identify the best haplotype construction method for use in QTLs detection studies, by comparing the three methods most commonly used for this purpose. Three simulated populations representing characteristics with three different heritability values were used for which the phenotypic, genotypic and pedigree data of the 6,000 animals were stored: Pop1 with low heritability (0.10); Pop2 with moderate heritability (0.25); and, Pop3 with high heritability (0.35). The simulated genomes consisted of 750,000 SNP-type markers, and 750 QTLs, with two to four alleles, arranged randomly on 29 chromosomes with a total size of 2,333 centimorgans (cM). From the simulation the SNPs whose frequency of the lowest allele was less than 0.1 were eliminated, leaving 576,027, 577,189 and 576,675 markers for Pop1, Pop2 and Pop3 populations, respectively. The phenotypic variation was 1.0 and the variation of QTLs was 50% of the heritabilities, for each population. The mean LD for each chromosome, measured by the D' statistic, ranged from 0.20 to 0.30 for all populations in the last generation. Haplotypes were constructed using three methods: Confidence Interval (CI), Four Gametes Rule (FGR) and Sliding-Window (SW). For Pop1, on chromosome 15, CI, FGR and SW methods identified five, eight and seven QTLs, respectively. Only one QTL was identified on chromosomes 19 and 29. For the high heritability characteristic, a QTL was identified on chromosome 11. Regarding the association analyzes using individual SNPs, four QTLs were identified on chromosome 15. For the moderate heritability characteristic, no significant isolated haplotypes or SNPs were found. The methodology of haplotype formation based on the FGR was considered the most efficient for the detection of QTLs in relation to CI and SW methods, as well as to the use of isolated SNPs.