| CPC G06Q 30/0202 (2013.01) [G06N 5/025 (2013.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06F 18/214 (2023.01)] | 20 Claims |

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1. A computer-implemented method comprising:
receiving, from a user device, customer information corresponding to a customer;
determining a set of vehicles, which is in an inventory of a vehicle dealership, that the customer is prequalified to purchase based on the customer information and a pricing model for financing the set of vehicles;
determining, using a machine learning model trained to approximate the pricing model based on historical output of the pricing model, a score for each vehicle within the set of vehicles based on the customer information and vehicle information for the set of vehicles, wherein the machine learning model is trained to approximate the pricing model with a threshold accuracy of less than 100% and prevented from training beyond the threshold accuracy, and wherein the score is determined based on an objective maximization function that maximizes both:
a first probability that the customer will purchase the vehicle, and
a second probability that a profitability of a sale price of the vehicle is agreeable to the vehicle dealership; and
generating a list of vehicles based on the set of vehicles, sorted by the score for each vehicle.
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