Abstract: Techniques are provided for multi-model prediction and resolution of order issues. An exemplary method for predicting issues that will delay an order comprises: obtaining features of the order; processing the features using a multi-model predictor to predict the issues that will delay the order, wherein the multi-model predictor comprises a first model that determines a probability that the order will be delayed and a second model that determines a probability that the order will be delayed for each of a plurality of different predefined order issue types; and aggregating an output of the first and second models to provide a likelihood of the issues that will delay the order. The multi-model predictor also optionally comprises a prediction model that predicts a number of the delay issues for a future time period and/or a cost of the delay issues for different predefined order issue types based on historical data.