This study addresses the critical need for precise reference evapotranspiration (ETo) estimation in Iraq, where limited climate data pose challenges for water management. The primary objective was to enhance accuracy in ETo estimation across diverse climates of Iraq by modifying Caprio (MC), Kharrufa (MK), and Penman (MP) models using metaheuristic optimization algorithms (particle swarm optimization and the marine predators algorithm). The modified models were validated using the historical observed data set (2012-2021) and ERA5 data sets (1959-2021). The results indicated that the MK, MC, and MP consistently outperformed their original estimates through comprehensive analyses, including statistical metrics, seasonal and monthly variations, probability distribution function, and spatial distribution patterns. The ranking results showed that the radiation-based MC equation, which considers air temperature and solar radiation, ranked first, followed by the temperature-based MK equation that relies only on air temperature, outperforming the mass transfer-based MP equation in various regions across Iraq, showing the superior performance of these models in accurately estimating ETo using air temperature and/or solar radiation. The study also found that while the MC and MK models are suitable for replicating the ETo of the standard Food and Agriculture Organization Penman-Monteith method in central and southern semiarid and arid regions, the MP model is more appropriate for the Mediterranean northern region.