A particular group of empirical methods used for mining design are classification systems, which attempt to relate the rock mass behaviour to an engineering application by capturing previous practical experiences. The main problem of using classification systems in block cave mining to predict cavability is that they are commonly applied without understanding the purposes of why they were developed, the basic assumptions and the limits established by the databases used to develop them. Most classification systems were originally developed for different purposes and may not contain the critical factors needed for a function for which they were not developed. More importantly, with time, the conditions from which these systems were developed would have changed, for instance mining depths today versus 50 years ago, noting that empirical methods cannot be extrapolated. There are two options for overcoming the problems of the use of current classification systems for cavability prediction: improve current methodologies or develop new techniques. The proposed research aims to develop a rock mass classification framework that captures the critical parameters governing cavability in block caving. Empirical methods will be used to quantify the geology influencing the rock mass behaviour, and numerical modelling parametric studies will be conducted to establish the degree of influence and sensitivity of the critical factors. Finally, statistics will be used to define the significance of the parameters to the rock mass behaviour and to establish the nature of combination of the factors to develop a single cavability prediction index. The presented poster is the result of the literature review, which establishes parameters qualitatively to be incorporated in a classification system to effectively assess cavability and establishes the research gaps in the state-of-the-art for cavability prediction.CITATION:Suzuki, K and Suorineni, F T, 2016. Review of the state-of-the-art in cavability prediction - the way forward, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), p 895 (The Australasian Institute of Mining and Metallurgy: Melbourne).