1. Historical data of the spring migration of the damson hop aphid Phorodon humuli recorded at Wye, Kent, and Rosemaund, Herefordshire, and the phenology of overwintering host-plant flowering, recorded at East Malling, Kent, were examined for possible associations. 2. Relationships between mean temperature over a phenophase interval, defined by flowering phenology of two overwintering host plum species (Myrobalan Prunus cerasifera and Victoria Prunus domestica), which are overwintering hosts for P. humuli, and the start of migration of the aphid, versus the reciprocal of the interval duration (days), were significant for Wye (situated 32 km from East Malling) and at Rosemaund, a more north-westerly site 260 km from East Malling. 3. Predictive sample reuse (PSR) methodology was used to validate the potential of derived models to predict the start of migration of P. humuli at the two sites. Data for model determination and validation consisted of observations of P. humuli migration over 20 years (1967-86) at Wye and 15 years (1972-86) at Rosemaund. 4. The predictive performance of the host-plant flowering- aphid migration phenology models was compared with that of two other methods that use historical field data to predict insect life cycle events. The host-plant flowering-aphid migration phenology model using the beginning of flowering of Victoria gave the best prediction of the start of migration at Wye using one PSR criterion. The empirical degree-day (DD) program gave the best prediction using an alternative criterion. For the more distant Rosemaund site, the empirical DD program performed best. 5. The potential use of host-plant phenology to predict 50% migration of P. humuli at Wye and Rosemaund was also investigated, and compared with the empirical DD programme using the PSR method. The host-plant phenology model gave good prediction of migration at Wye but poor prediction at Rosemaund, whereas the empirical DD programme gave poor prediction at Wye and only reasonable prediction at Rosemaund. 6. The value of using historical data of host-plant and insect phenology to develop predictive models is illustrated, and the desirability of comparing the performance of alternative phenology models that may be used for prescriptive use is discussed