Abstract: When evaluating the emergency management capability of coal mines, the process of assigning weights to indicators can easily result in missing data values, leading to poor calculation accuracy of indicators and affecting the accuracy of evaluation results. To this end, comprehensive evaluation model for coal mine emergency management capability based on ART-2 artificial neural network algorithm is constructed to enhance the objectivity and accuracy of the evaluation. Firstly, based on the structure of the coal mine emergency management system, the scoring values are standardized and converted into a set of category sample vectors. Provide standardized data input for the subsequent use of ART-2 artificial neural network algorithm for indicator screening. Secondly, the ART-2 artificial neural network algorithm is used to screen the indicators of coal mine management capability. Thirdly, the elements in the network hierarchy are combined to construct an unweighted matrix of the mutual influence between evaluation indicators. This matrix comprehensively reflects the correlation between various evaluation indicators, providing a basis for subsequent weight allocation. Set warning values at the target layer neuron nodes and train and optimize the unweighted matrix using ART-2 artificial neural network. During this process, the algorithm can automatically adjust and correct the weights of indicators, reducing the subjectivity and ambiguity of weight allocation. Finally, based on the revised weights, the index scores at each layer of neuron nodes are recalculated to obtain the final evaluation result. The research conclusion shows that the coal mine emergency management capability evaluation model based on ART-2 artificial neural network algorithm has significant advantages in solving the problems of subjective weight allocation and easy data loss in traditional evaluation methods. It can provide more scientific and reasonable basis for coal mine emergency management decision-making, help coal mining enterprises better evaluate and improve emergency management capabilities, and thus ensure the safety production of coal mines.