Mapping quantitative trait loci (QTLs) is usually conducted with a single line cross. The power of such QTL mapping depends highly on the two parental lines. If the two lines are fixed for the same allele at a putative QTL, the QTL is undetectable. On the other hand, if a QTL is segregating in the line cross and is detected, the estimated variance of the QTL cannot be extrapolated beyond the statistical inference space of the two parental lines. To reduce the likelihood of missing a QTL and to increase the statistical inference space of the estimated QTL variance, we present a consensus QTL mapping strategy. We adopt the identical by descent (IBD)-based variance component method originally applied to human linkage analysis by combining multiple line crosses as independent families. We explore the properties of consensus QTL mapping and demonstrate the method with F2, backcross (BC), and full-sib (FS) families. In addition, we examine the effects of the QTL heritability, marker informativeness, QTL position, the number of families, and family size. We show that F2 families notably outperform BC and FS families in detecting a QTL. There is a substantial reduction in the standard deviation of the estimated QTL position and the separation of the QTL and polygenic variance. Finally, we show that the power to detect a QTL is greater when using a small number of large families than a large number of small families.