The three datasets considered in this study have all been previously analyzed using alternative (more standard) statistical methods and the results published elsewhere (13, 15, 17). In brief, previously, we presented controlled observations of 6- to 8-week-old puppy behavior, the Puppy Profiling Assessment (PPA), where three (stroking, fake prey, ramp) of seven stimuli presented (also including following, retrieve, gentle restraint, noise, tunnel) could be usefully combined and associated with whether dogs completed guide dogs training to become a working guide dog (success) (17). Reactions to these stimuli could be applied to identify a small number of dogs that were later withdrawn from guide dog training with high specificity but low sensitivity, and a subsequent study suggested responses to stimuli were heritable (18). Using a questionnaire approach, completed by Guide Dog staff for trainee guide dogs of 5, 8, and 12 months of age, seven behavior traits were identified, adaptability; body sensitivity; distractibility; excitability; general anxiety; trainability and stair anxiety, which all showed associations with later success in guide dog training (15). Together, the traits could be applied to early identify a small proportion of dogs with high specificity that were later withdrawn and which were successful. A final relevant publication considered dogs withdrawn from service as a guide dog for behavior reasons based on retrospective data (13). We found that there was no peak in working life in which dogs were withdrawn for behavior, and sex and breed were important factors in age of behavioral withdrawal. In all cases, the statistical methods used to explore the association with later success in guide dog training or withdrawal from training or working were based on variants of logistic regression models. Here, we extend analysis from these three studies to include the entire span of a guide dog from training to retirement for the retrospective dataset [hence overlapping but not identical data between this paper and (13)]. The aim is to illustrate the utility of survival analysis and multistate modeling and to explore the additional insights these methods provide beyond more traditional methods of analysis.