Reinforcement learning (RL) models are increasingly being deployed in complex three-dimensional environments. These spaces often present unique difficulties for RL methods due to the increased degrees of freedom. Bandit4D, a cutting-edge new framework, aims to mitigate these challenges by providing a flexible platform for training RL agents in 3D s