Background: A prediction model including age, self-rated health (SRH) and prior sickness absence (SA) has previously been found to predict frequent SA. Aims: To further validate the model and develop it for clinical use.Methods: A multicentre study of care of the elderly workers employed at one of 14 centres in Aarhus (Denmark). SA episodes recorded in the year prior to baseline and both age and SRH at baseline were included in a prediction model for frequent (three or more) SA episodes during a 1-year follow-up period. The prediction model was developed in the largest centre. Risk predictions and discrimination between high- and low-risk workers were investigated in the other centres. The prediction rule 'SRH-prior SA' was derived from the prediction model and prognostic properties of the prediction rule were investigated for each centre, using score <0 as cut-off. Results: Of 2562 workers, 1930 had complete data for analysis. Predictions were accurate in 4 of 13 centres; discrimination was good in five and fair in another five centres. Prediction rule scores <0 identified workers at risk of frequent SA with sensitivities of 0.17-0.54, specificities of 0.86-0.96 and positive predictive values of 0.54-0.87 across centres. Conclusions: The prediction model discriminated between workers at high and low risk of frequent SA in the majority of centres. The prediction rule 'SRH-prior SA' can be used in clinical practice specifically to identify workers at high risk of frequent SA.