Healthcare demand is growing in Australia and across the world. In Australia, the healthcare system comprises a mix of private and public organizations, such as hospitals, clinics, and aged care facilities. The Australian healthcare system is quite affordable and accessible because a large proportion of the expenditure, around 68%, is funded by the Australian government. The healthcare expenditure in 2015-16 was AUD 170.4 billion which was 10.0% of the GDP. Soaring healthcare costs and growing demand for services are increasing the pressure on the sustainability of the government-funded healthcare system. To be sustainable, we need to be more efficient in delivering healthcare services. We can schedule the care delivery process optimally and subsequently improve the efficiency of the system if demand for services is well known. However, there is a randomness in demand for services, and it is a cause of inefficiency in the healthcare delivery process. Soaring healthcare costs and the growing demand for services require us to use healthcare resources more efficiently. Randomness in resource requirements makes the care delivery process less efficient. Our aim is to reduce the uncertainty in patients’ resource requirements, and we achieve that objective by classifying patients into similar resource user groups. The conventional random forest., k-nearest neighbourhood (KNN) methods were resulted in poor classification, prediction performance.