BACKGROUND: The length of the gonotrophic cycle varies the vectorial capacity of a mosquito vector and therefore its exact estimation is important in epidemiological modelling. Because the gonotrophic cycle length depends on temperature, its estimation can be satisfactorily computed by means of physiological time analysis. METHODS: A model of physiological time was developed and calibrated for Anopheles pseudopunctipennis, one of the main malaria vectors in South America, using data from laboratory temperature controlled experiments. The model was validated under varying temperatures and could predict the time elapsed from blood engorgement to oviposition according to the temperature. RESULTS: In laboratory experiments, a batch of An. pseudopunctipennis fed at the same time may lay eggs during several consecutive nights (2-3 at high temperature and > 10 at low temperature). The model took into account such pattern and was used to predict the range of the gonotrophic cycle duration of An. pseudopunctipennis in four characteristic sites of Bolivia. It showed that the predicted cycle duration for An. pseudopunctipennis exhibited a seasonal pattern, with higher variances where climatic conditions were less stable. Predicted mean values of the (minimum) duration ranged from 3.3 days up to > 10 days, depending on the season and the geographical location. The analysis of ovaries development stages of field collected biting mosquitoes indicated that the phase 1 of Beklemishev might be of significant duration for An. pseudopunctipennis. The gonotrophic cycle length of An. pseudopunctipennis correlates with malaria transmission patterns observed in Bolivia which depend on locations and seasons. CONCLUSION: A new presentation of cycle length results taking into account the number of ovipositing nights and the proportion of mosquitoes laying eggs is suggested. The present approach using physiological time analysis might serve as an outline to other similar studies and allows the inclusion of temperature effects on the gonotrophic cycle in transmission models. However, to better explore the effects of temperature on malaria transmission, the others parameters of the vectorial capacity should be included in the analysis and modelled accordingly.