The accuracy of minimum post-mortem interval (mPMI) estimates usually hinges upon the ability of forensic entomologists to predict the conditions under which calliphorids will colonise bodies. However, there can be delays between death and colonisation due to poorly understood abiotic and biotic factors, hence the need for a mPMI. To quantify the importance of various meteorological and light-level factors, beef liver baits were placed in the field (Victoria, Australia) on 88 randomly selected days over 3 years in all seasons and observed every 60-90 min for evidence of colonisation. Baits were exposed during daylight, and the following parameters were measured: barometric pressure, light intensity, wind speed, ambient temperature, relative humidity and rainfall. Collected data were analysed using backward LR logistic regression to produce an equation of colonisation probability. This type of analysis removes factors with the least influence on colonisation in successive steps until all remaining variables significantly increase the accuracy of predicting colonisation presence or absence. Ambient temperature was a positive predictor variable (an increase in temperature increased the probability of calliphorid colonisation). Relative humidity was a negative predictor variable (an increase in humidity decreased the probability of calliphorid colonisation). Barometric pressure, light intensity, wind speed and rainfall did not enhance the accuracy of the probability model; however, analysis of species activity patterns suggests that heavy rainfall and strong wind speeds inhibit calliphorid colonisation.