The U.S. aquaculture industry faces inherent production, marketing, and financial risks. In 2023, foodfish, sportfish, and baitfish together accounted for approximately 48% of the sector’s total value. Economic risk analysis involves quantifying measurable variations in risky factors by assigning mathematical probabilities and later measuring their fluidity on farm profits and cost of production. This study presents the first comprehensive farm-level economic risk assessment of U.S. aquaculture, evaluating multiple key species such as catfish, hybrid striped bass, red drum, trout, largemouth bass, tilapia, golden shiner, fathead minnow, and various sportfish (Fig. 1) across diverse production systems and scales. Enterprise budgets built using aggregate farm data were standardized to 2024 values. Monte Carlo simulations (2,000 iterations) were used in Crystal Ball® to generate cumulative and reverse cumulative distributions, tornado charts (depicting rank order of risk factors), and sensitivity measures (Spearman’s rank correlation) across three dynamic price scenarios of fish and feed prices: a 10-yr long run average price conditions, a medium 3-year average price conditions, and a 1 yr short run average price conditions. Forecast variables include net return, break-even price, and yield above variable and total costs, with 11 assumption variables defined per species (Fig. 2). Results identify species, systems, and scales with the greatest and least economic risk, as well as the most influential risk drivers of outcomes. These findings provide essential insights to develop risk management strategies for fish farmers, policymakers, and insurers