CONTEXT: Agriculture is a cornerstone of Uzbekistan's economy, accounting for 25 % to the national gross domestic product and employing 26 % of the workforce. Since independence, wheat intensification has been a national priority, with cultivated land expanding from 0.63 million hectares (Mha) to 1.24 Mha and productivity increasing from 1.66 t ha-1 in 1991 to 4.55 t ha-1 in 2023. However, on-farm yields remain below attainable yield, leading to a reliance on wheat imports to meet domestic demand. Closing this yield gap is critical for achieving national wheat self-sufficiency. OBJECTIVES: This study aims to identify key yield-limiting factors and develop evidence-based, agroecologically optimized bundled solutions to enhance wheat productivity in Uzbekistan. By integrating multiple analytical approaches, the research seeks to provide targeted agronomic recommendations for improving sustainability and self-sufficiency. METHODS: A combination of systematic reviews, crop modeling, and machine learning was used to analyze wheat yield gaps and optimize agronomic practices. Agricultural Production Systems sIMulator (APSIM) -Wheat model was calibrated, validated and used to simulate wheat yields over 36-years across four agro-ecological zones (AEZs): Khorezm (arid saline lowland), Kashkadarya (semi-arid highland), Samarkand (semi-arid mid altitude), and Jizzakh (arid high-altitude). The simulations optimized seeding dates, nitrogen fertilizer rates, cultivar selection, and water management practices. Additionally, a meta-analysis of 90 studies and machine learning were employed to identify key determinants of wheat yield variation. RESULTS AND CONCLUSIONS: To achieve self-sufficiency, Uzbekistan requires an average wheat yield of 6.62 t ha-1, necessitating a 45 % (2.07 t ha-1) increase from current levels (4.55 t ha-1), while the yield gap of 3.25 t ha-1 exists. The study identified nitrogen fertilization, irrigation, rainfall, cultivar selection, and seeding dates as the primary determinants of yield. Wheat yield declined significantly when plant-available water content dropped below 50 %, establishing a critical threshold for sustainable productivity. Precision nutrient management included applying 150-180 kg N ha-1, up to 120 kg PRO5 ha-1, and 75 kg KRO ha-1. Conservation agriculture showed a 26 % increase in yields compared to conventional tillage. High-yielding, stress-tolerant wheat varieties released after 2010 increased wheat productivity by up to 22 %. Seeding between September 15 and October 15 maximized yields, while delayed sowing reduced yield by up to 57 kg ha-1 day-1. Seed rates of 160-180 kg ha-1 improved plant density and yields, preventing excessive competition or underutilization. SIGNIFICANCE: This study offers a science-based framework for improving wheat productivity in Uzbekistan through AEZ-specific, resource-efficient bundled solutions. By integrating crop modeling, machine learning, and systematic reviews, this study provides scalable solutions to enhance input use efficiency, resilience to climate