Predicting the flowering times of angiosperm taxa is a goal of mounting importance in the face of future climate change, with applications not only in plant biology and ecology, but also in invasive species management, horticulture, and agriculture. To date, no tool is available to facilitate predictions of flowering phenology based on multivariate phenoclimatic models. Such a tool is needed for researchers and other stakeholders who need to predict phenological activity, but who are unfamiliar with phenoclimate modelling techniques. PhenoForecaster remedies this deficiency by allowing users of any background to conduct species-specific phenological predictions of mean flowering date (MFD) using an intuitive graphical interface. Required input consists of species of interest, as well as five climate parameters pertaining to the year and location for which estimates of MFD are desired: the date on which the annual frost-free period began, the quantity of precipitation which fell as snow during the winter and spring seasons, and the number of frost-free days during the winter and spring seasons. Output consists of estimated mean flowering date for the selected species under the selected conditions. Bulk prediction is possible using comma delimited files that include all relevant climate information.