The assessment of animal welfare can include resource-based or animal-based measures. Official animal welfare inspections in Denmark primarily control compliance with animal welfare legislation based on resource measures (e.g. housing system) and usually do not regard animal response parameters (e.g. clinical and behavioural observations). Herds selected for welfare inspections are sampled by a risk-based strategy based on existing register data. The aim of the present study was to evaluate register data variables as predictors of dairy herds with violations of the animal welfare legislation (VoAWL) defined as occurrence of at least one of the two most frequently violated measures found at recent inspections in Denmark, namely (a) presence of injured animals not separated from the rest of the group and/or (b) animals in a condition warranting euthanasia still being present in the herd. A total of 25 variables were extracted from the Danish Cattle Database and assessed as predictors using a multivariable logistic analysis of a data set including 73 Danish dairy herds, which all had more than 100 cows and cubicle loose-housing systems. Univariable screening was used to identify variables associated with VoAWL at a P-value<0.2 for the inclusion in a multivariable logistic regression analysis. Backward selection procedures identified the following variables for the final model predictive of VoAWL: increasing standard deviation of milk yield for first lactation cows, high bulk tank somatic cell count (⩾250 000 cells/ml) and suspiciously low number of recorded veterinary treatments (⩽25 treatments/100 cow years). The identified predictors may be explained by underlying management factors leading to impaired animal welfare in the herd, such as poor hygiene, feeding and management of dry or calving cows and sick animals. However, further investigations are required for causal inferences to be established.