Coffee flowering data were analyzed in order to explore the effect of two environmental variables that have been considered relevant for this process. Pre-anthesis stage flowers were counted in coffee leaf-rust resistant crops at eight experimental stations (between 2°N and 11°N). Likewise, climatic data were taken to generate a humidity soil index, whereas day longitude data were taken from the Smithsonian Meteorological Tables. Flowering data were compared with a sunshine index to understand better the effect of light on flowering. This data (flowering, soil humidity index and day length) were expressed in a monthly scale and analyzed using linear regression and cross-correlation functions. The main results show that there is a significant correlation between short days and high flowerings, whereas soil humidity (dry months) are related to the phenomenon, but to a lesser extent.