Background/Question/Methods Wildlife managers making decisions that balance species conservation and human development often are faced with uncertainty about where specific actions may occur, complicating the ability to robustly quantify expected impacts. Decisions must nonetheless be made despite uncertainty. This reinforces the importance of methods to quantify the range of expected uncertainty between different management options to inform the decision process. We present the Development Impacts Analysis (DIA), which uses a Monte Carlo approach to simulate future development under a range of alternatives and predict expected impacts to various wildlife taxa. We apply the DIA to five oil leasing alternatives in the National Petroleum Reserve – Alaska (NPR-A). For each alternative, oil production pads and roads were randomly simulated in proportion to estimated undiscovered oil and alternative-specific development constraints. We calculated high-quality habitat loss for two caribou herds and nine bird species based on published responses to development and human activity, repeating the process 100 times for each alternative to capture a range of uncertainty. Results/Conclusions The Teshekpuk Caribou Herd and seven of the eight shorebird species showed the most habitat loss with the alternative with the greatest area available for leasing and development. However, the Western Arctic Herd showed greatest loss with the no-action alternative, which featured one of the lowest areas available for development. This likely relates to the spatial configuration of leasing prohibitions, which failed to include the northern part of the herd’s core calving area under the no-action alternative. Molting brant only showed impacts under the two alternatives that made the most area available for development, though these results were affected by a limited sampling area. Brant molt elsewhere in the NPR-A, likely increasing impacts for all alternatives. The order of habitat loss across the alternatives varied among species, emphasizing the likelihood of management tradeoffs for different species. Our results demonstrated the potential of simulation modeling to account for uncertainty while exploring potential effects of future development. While we apply the DIA to compare leasing alternatives in the NPR-A, it is equally applicable for other management decisions with spatially explicit ecological data and development alternatives.