Importance The substantial variation and excess of supplies requested by surgeons for each case using surgical preference cards represents an opportunity for cost reduction through optimization. Objective To optimize preference cards based on historical supply use captured through surgical receipts. Design, Setting, and Participants This quality improvement study took place in a large, tertiary, multi-hospital academic health system from January 1, 2019, through December 31, 2023. It included urology, colorectal, and surgical oncology services. These data were analyzed from January 2024 to August 2024. Exposures Separate linear time-series ordinary least squares regression models were fit for each surgical receipt item to estimate the optimal number of that item based on data from past cases between January 1, 2019, and December 31, 2023. Optimal surgical preference cards were constructed and compared after collating item-level estimates by optimizing items listed on existing surgical preference cards, creating new preference cards for each procedure, and creating new preference cards that stratify existing preference cards by procedure. Main outcome and measures The number of unique and total items on the cards before and after optimization were calculated at the 3 levels. Baseline waste was estimated in existing preference cards as the difference between the total cost of all items on the current surgical preference card and total cost of the surgical receipt associated with the case, averaged across all eligible cases from January 1, 2024, to May 31, 2024. Baseline waste was also compared against the estimated waste, using the optimized surgical preference card at each of the 3 levels. Results A total of 1298 preference cards and 432 procedures were evaluated, accounting for 3088 unique preference card–procedure combinations. The current surgical preference cards incurred a mean (SD) cost per case of unused items of $1294.41 ($2307.17), amounting to $3 716 251.11 across all cases in the study. All 3 optimization strategies reduced the cost of unused items and produced less intraoperative burden. The greatest relative reduction in the cost of unused items was seen in colorectal surgery, where cost savings of $488 774.88 reflected a 55.8% reduction. Conclusions and Relevance Optimization of surgical preference cards with regression models has the potential to reduce surgical waste, with the greatest reduction in waste seen with optimizing existing cards after stratifying at the procedure level.