Property investment is always enticing, especially the high-rise residential property. The promise of the raising future value of it keeps investors attracted. Urbanisation also contributes to the massive development in this business, and it is hardly ignored. To run the business and to be able to compete with others, developers have to keep the cost attracted for the residents/buyers. The property needs to be well designed to satisfy the economical capital expenditure as well as low operation and maintenance cost. The high density of this development in an urban area makes developers tend to have low awareness of practising sustainability. Inconsistent evaluation, as well as unwell-defined assessment for sustainability, worsen the situation. This research aims to investigate and develop performance evaluation criteria of sustainability for high-rise residential building. Both qualitative and quantitative approaches were implemented through surveys. Three main factors, which are the promotion of a healthy environment, comfortability of residents and energy-saving, found to be the main categories of criteria to be considered. Based on validation through a case study, it is found that providing easy access to public transport is the most critical criteria for promoting a healthy environment. Besides, the usage of low Volatile Organic Compound (VOC) paint can give comfort to residents because it provides healthy indoor air quality. Lastly, the usage of LED bulbs and natural light supports energy saving. The criteria are then used to develop the decision-making model in selecting the best alternative for the building refurbishment, by using Analytical Hierarchy Process (AHP). Application of the decision model in a case study reveals that repainting the building using low VOC paint become the best fit option for enhancing the environment. Developers may implement this in their policy for the redevelopment of their building. The result is limited to the aggregation value; thus, future research is directing into coalition and negotiation among stakeholders by applying payoff optimum and agreement options and also automation in selecting the best technical solution. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.