Recent developments in the global rare earth elements (REE) sector have caused a surge in motivation for nations outside of China to secure their own REE supply. However, the volatility of this sector is hindering most of these projects from reaching production. The aim of this study is to address one of these major sources of risk: the inherent geological uncertainty of REE deposits. By deterministically estimating ore quality and assuming the distribution of REEs present in a deposit using the total rare earth oxide (TREO) grade, a mine planner does not have the necessary resolution to properly assess these risks and inform their decisions. As a result, the mine production schedule will not maximize the generation of cash flows nor meet the expected production targets. Better representation of a REE deposits' spatial variability and uncertain characteristics, coupled with advancements in the field of stochastic mine planning, can offer the tools to develop a mine design that will yield a higher NPV while ensuring a better performance in terms of achieving ore tonnage, ore grade and desired blend of REE mineralization goals. The application herein will consist of the joint conditional simulation of the 14 stable Lanthanides and Yttrium present in a monazitic REE deposit. Multiple realizations of this deposit are used to develop a risk resilient mine production schedule that will maximize NPV while ensuring consistent ore grades and REE blends at the head of the mill.