The purpose of this study was to determine whether broiler mortality is influenced by selection on correlated traits, determine the accuracy of genetic evaluation for mortality with traditional and genomic evaluations, and determine whether the use of the multi-trait model increases the accuracy of predictions. Phenotypes were available on 181,022 broilers for up to 8 traits, 4 linear and 4 categorical. Pedigree was available for 186,596 broilers and genotypes were available on 18,047 animals. For linear traits the model included the fixed effects of sex and contemporary group, random direct genetic, and maternal genetic effect for body weight. Contemporary group is the grouping of source, mini-generation and hatch. For categorical traits, the contemporary group was treated as random and a fixed effect of generation was added. (Co)variance components were estimated with a Gibbs sampling program THRGIBBS1F90 for threshold-linear models. A traditional BLUP using a pedigree relationship matrix and a genomic BLUP (ssGBLUP) using a combined pedigree-genomic relationship matrix were used to predict EBV and genomic EBV, respectively. Because few dead animals were genotyped, the traditional validation techniques did not apply. Subsequently models were compared using a data splitting technique based on the correlation of EBV from 2 non-overlapping samples, each one with one-half of the phenotypes selected across contemporary groups. The correlations were computed only for genotyped animals in the last generation and are measures of realized accuracy. The genetic correlation between mortality and the other traits were generally small (absolute value < 0.15), with notable differences for maternal body weight (−0.50) and Ascites (0.77); heritability for mortality was 13%. The correlations between independent samples in a univariate model for mortality were 0.59 for the non-genomic and 0.64 for the genomic model. In a multiple trait genomic model, the correlations increased by 0.09 over single trait genomic model. Results indicate mortality may be more affected by ascites and maternal growth compared with other traits under selection. Use of the genomic data increases the accuracy of genetic evaluation for mortality.