Single-select predictive platform model

A system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform functions comprising:
• determining, by a machine-learning model, a probability that a user will re-order a set of items within a period of time by using previous transactions of the user and other users over a previous period of time as input and outputting a re-order likelihood score attributed to each item of the set of items as ordered at a present time, wherein the machine-learning model is trained on training data received, as refreshed during a second period of time;
• determining the set of items to recommend to the user based on the probability exceeding a predetermined threshold that the user will re-order each item of the set of items at the present time;
• sending instructions to display the set of items to the user on a user interface, wherein at least a portion of the set of items is shown as selected on the user interface, and the user interface further comprises a single-click option to add to a cart all selected items of the set of items;
• receiving a selection of the single-click option to add to the cart the all selected items of the set of items;
• and
• after receiving the single-click option, adding the all selected items of the set of items to the cart.