A model was constructed to predict monthly birth probabilities using mammalian fertility data. We used a sample of 147 female capybaras (Hydrochoerus hydrochaeris) hunted on a farm on Marajó Island, Brazil. In the model each month was treated as a multinomial with six cells representing the six possible reproductive states (five months gestation). A hypothesis test was carried out to see whether a cosine curve would fit the birth probabilities. The results offer no support for a seasonal component (F2,9 = 1.84, P = 0.21), whereas results from a direct census do (F3,23 = 87.29, P < 0.01). Some hunting techniques were biased towards killing pregnant females (χ(2)1= 7.2, P< 0.01), thereby spreading reproduction throughout the year (F2,9 = 1.84, P = 0.21). The model remained a powerful predictive tool to be used with mammalian fertility data as long as the data are not biased towards pregnant females.