Sugarcane (Saccharum spp. L.) cropping systems require the application of substantial amounts of fertiliser nitrogen (N), especially under irrigated conditions and in areas where rainfall is sufficient for high dry matter production. Inadequate N applications can reduce yields, while excess N or inappropriately timed applications can result in the export of significant quantities of N to the environment as a pollutant. An N subroutine has now been included into the Canegro crop model which is based in the DSSAT (Decision Support System for Agrotechnology Transfer) framework. Data from a field and lysimeter trial conducted in Pongola, South Africa were used to calibrate and evaluate the model, following which the model was used to investigate two potential approaches to improve fertiliser N management. Findings were, firstly, that measured and simulated results show on-farm monitoring of soil inorganic N levels and adjusting fertiliser applications accordingly has considerable potential for reducing fertiliser requirements and N losses. Secondly, during the periods between active crop growth cycles, significant amounts of inorganic N can accumulate in a soil as a result of mineralisation. Accounting for this N enables fertiliser N application to be delayed to some time after planting or commencement of ratoon growth, thereby significantly reducing the risky period during which applied N may be leached. For the system modelled in this study, inorganic N made available through organic matter mineralisation was sufficient to match initial crop demand for *55 days following ratooning. When ammonium-based fertilisers are used, lower volatilisation losses can also be expected with this strategy. These findings now need to be confirmed in field trials. Modelling, combined with adequate measured data for calibration purposes, can be a powerful tool to identify improved N management practices for a particular cropping system. In its current form, Canegro-N can be used to improve our understanding of N dynamics in sugarcane production systems and to guide management practices and future research.