A historical phenological record and meteorological data of the period 1960-2009 are used to analyse the ability of seven phenological models to predict leaf unfolding and beginning of flowering for two tree species-silver birch Betula pendula and bird cherry Padus racemosa-in Latvia. Model stability is estimated performing multiple model fitting runs using half of the data for model training and the other half for evaluation. Correlation coefficient, mean absolute error and mean squared error are used to evaluate model performance. UniChill (a model using sigmoidal development rate and temperature relationship and taking into account the necessity for dormancy release) and DDcos (a simple degree-day model considering the diurnal temperature fluctuations) are found to be the best models for describing the considered spring phases. A strong collinearity between base temperature and required heat sum is found for several model fitting runs of the simple degree-day based models. Large variation of the model parameters between different model fitting runs in case of more complex models indicates similar collinearity and over-parameterization of these models. It is suggested that model performance can be improved by incorporating the resolved daily temperature fluctuations of the DDcos model into the framework of the more complex models (e.g. UniChill). The average base temperature, as found by DDcos model, for B. pendula leaf unfolding is 5.6 °C and for the start of the flowering 6.7 °C; for P. racemosa, the respective base temperatures are 3.2 °C and 3.4 °C.