Process-oriented crop growth models can be useful in simulating daily crop growth and development rates through the growing season. The strength of these models is their ability to integrate the effects of temporal and multiple stresses on crop growth under different environmental and management conditions. CROPGRO-Cotton model has been extensively tested and validated in many studies, mainly in United States. The objective of this study was to test and validate CROPGRO-Cotton model in a cotton growing region of south east Australia. The model was calibrated and validated using data from a cotton field experiment conducted during 2008 and 2009 at the Kingsthorpe experimental station of Agri-Science Queensland. The station is located in the southern part of Queensland, Australia, in a sub-tropical climate (Latitude South 27°30’44.5”; Longitude East 151°46’54.5”; 431 m above mean sea level). The field experiment used a randomised complete block design with four irrigation treatments and three replications with optimal nitrogen fertiliser inputs. The model was first calibrated using the well irrigated treatment with measurements of developmental stages, harvested grain yield, crop biomass, and soil water content. It was validated against the same measurements for deficit-irrigation treatments. The model was further tested using lint yield data from other sites located in south east Queensland and northern New South Wales. Lint yield was well simulated for all the treatments (Root Mean Square Error= 100 kg ha-1 for the 2008 growing season and 254 kg ha-1 for the 2009 growing season).When the model was run in different locations between south east Queensland and northern New South Wales it accurately simulated cotton yield (y= 0.75x +218.2; r2= 0.79; RMSE= 395.3 kg ha-1).