Mortality due to feather pecking (FP) has large economic and welfare consequences in the commercial poultry industry, and reduces survival of birds. With FP, the survival time of a hen depends both on her own genetic ability to avoid becoming the victim of FP (direct genetic effect; DGE), and on the genetic tendency of her group mates to perform FP (indirect genetic effect; IGE). Thus, to improve survival time of laying hens, it is important to use a breeding strategy that captures both the DGE and the IGE of selection candidates. Here, we investigate the prospects for solving mortality due to FP in laying hens by genetic selection. First, we review genetic parameters for survival time. Second, we use deterministic simulation to predict response to selection for 2 multi-trait crossbred breeding programs, a traditional recurrent testing scheme (RT) and a genomic selection scheme (GS). Finally, we investigate the prospects for sustained improvement of survival time when mortality becomes low. Results show that survival time has considerable heritable variation; most estimates of the total additive genetic standard deviation are larger than 1 mo. As expected, predicted single generation response to selection in survival time with GS is substantial larger than with RT. Particularly when the correlation between survival time and other breeding goal traits is zero, the GS scheme yields substantial improvement in survival time. For example, when mortality is 35%, the genetic correlation between survival time and other traits is 0, allowing for a 10% reduction of response in other traits, and when selection takes place in both the sire line and dam line, survival time can be improved with ∼23 D in one generation, using GS. Results, however, also show a strong decrease in heritability when mortality decreases, indicating that continued improvement becomes increasingly difficult. In summary, our results show that breeders can considerably reduce mortality due to FP with limited reduction of improvement in other breeding goal traits.