Identifying memory block write endurance using machine learning

Systems and methods are described for predicting an endurance of groups of memory cells within a memory device, based on current characteristics of the cells. The endurance may be predicted by processing historical information regarding operation of memory devices according to a machine learning algorithm, such as a neural network algorithm, to generate correlation information between characteristics of groups of memory calls at a first time and an endurance metric at a second time. The correlation information can be applied to current characteristics of a group of memory cells to predict a future endurance of that group. Operating parameters of a memory device may be modified at a per-block level based on predicted block endurances to increase the speed of a device, the longevity of a device, or both.