Birth seasonality responds to a variety of environmental and socio-cultural factors. The present study was carried out to quantify the trends in seasonal variation in birth rate in seven districts in the Kayes region of Mali between 2007 and 2010 and to attempt to link climatic- and agricultural-cycle-dependent factors with birth seasonality. Lagged regression analysis based on time series analysis techniques was used to investigate seasonality of births registered in health facilities and its association with climate, labour migration, agriculture workload, malaria infection and food supply. There was a clear bimodal pattern in month-to-month institutional delivery rate variation, and this seasonal pattern repeated each year over the study period. The data showed that rates of health-facility-attended deliveries were high at the end of the dry season (April-June), fell rapidly in the first half of the rainy season, rose again during the later part of the rainy season (August-October) and fell to their lowest values after the rains. The first peak observed in spring (April-June) corresponded to conception nine months earlier during the rainy season (between July and September), while the second peak observed in the third quarter of the year (August-October) corresponded with conception at the beginning of the dry season right after the harvest period (between November and January). Between these peaks was an abrupt trough in July. The findings support a causal process through which climate change influences conception/birth seasonality in two direct and indirect pathways. On one side climate change influences conception/birth seasonality from the effects on fetal loss (changes in annual rainfall leading to changes in malaria incidence) and on the other side by affecting fecundability (changes in agricultural cycles leading to changes in food production, agricultural workload and socio-cultural events, which in turn influence energy balance and sexual behaviour). Labour migration, which is closely linked with the agricultural cycle, influences sexual intercourse and thus marital fertility. Finally, the model emphasizes an eco-systemic approach to the study of birth seasonality.