Mining industries monitor mining dilution and operating costs as key performance indicators in comparing efficiency of mining operations. These variables are continuously measured by comparing the planned variables to the actuals that were achieved. For instance, key performance variables such as throughput, grade, recovery and cash flow are closely monitored and variance between planned and actual gives indication of process improvement. The effect of dilution manifest in several ways. Firstly, mining dilution can significantly impact metal recovery and grade. For instance, when ore is diluted, the concentration of valuable metals in the ore decreases. The financial viability of a mining operation can be affected through waste processing with further links to poor downstream process performance. Although, data-based upstream mining predictive modelling has gained recognition in recent times, understanding the cause and effect in complex mining variables in industrial data set is still green. The research question that still require further studies is what variables are causing mining dilution. The objective of this study is to establish a reliable relationship among mining variables impacting on dilution. Real industrial data set will be used together with simulations, considering tonnes, grade, equivalent linear overbreak/slough, drill spacing and drill metres.