The migration of cereal aphids and the time of their arrival on winter cereal crops in autumn and spring are of particular importance for plant disease (e.g. barley yellow dwarf virus infection) and related yield losses. In order to identify days with migration potentials in autumn and spring, suction trap data from 29 and 45 case studies (locations and years), respectively, were set-off against meteorological parameters, focusing on the early immigration periods in autumn (22 September to 1 November) and spring (1 May to 9 June). The number of cereal aphids caught in a suction trap increased with increasing temperature, global radiation and duration of sunshine and decreased with increasing precipitation, relative humidity and wind speed. According to linear regression analyses, the temperature, global radiation and wind speed were most frequently and significantly associated with migration, suggesting that they have a major impact on flight activity. For subsequent model development, suction trap catches from different case studies were pooled and binarily classified as days with or without migration as defined by a certain number of migrating cereal aphids. Linear discriminant analyses of several predictor variables (assessed during light hours of a given day) were then performed based on the binary response variables. Three models were used to predict days with suction trap catches ≥1, ≥4 or ≥10 migrating cereal aphids in autumn. Due to the predominance of Rhopalosiphum padi individuals (99.3% of total cereal aphid catch), no distinction between species (R. padi and Sitobion avenae) was made in autumn. As the suction trap catches were lower and species dominance changed in spring, three further models were developed for analysis of all cereal aphid species, R. padi only, and Metopolophium dirhodum and S. avenae combined in spring. The empirical, cross-classification and receiver operating characteristic analyses performed for model validation showed different levels of prediction accuracy. Additional datasets selected at random before model construction and parameterization showed that predictions by the six migration models were 33–81% correct. The models are useful for determining when to start field evaluations. Furthermore, they provide information on the size of the migrating aphid population and, thus, on the importance of immigration for early aphid population development in cereal crops in a given season.