<p>This study was conducted to determine and optimize energy indices and greenhouse gas emissions, as well as to perform an economic analysis of sugar beet production using Data Envelopment Analysis (DEA). The required data were collected through interviews with farmers and agricultural experts in Eyvan County, Ilam Province of Iran, as well as via structured questionnaires. The results indicated that the total energy input and output were 45,211.99 and 1,093,411.2 MJ ha⁻¹, respectively. Regression coefficients revealed that human labor, machinery, phosphorus and potassium fertilizers, and also manure had a positive effect on crop yield, whereas electricity, nitrogen fertilizer, and diesel fuel had a negative impact. The Greenhouse Gas (GHG) emission analysis indicated that, under conventional practices, nitrogen fertilizer and diesel fuel contributed 620.19 and 606.24 kg CO₂-eq, respectively; after optimization, these values were reduced to 561.54 and 438.74 kg CO₂-eq. DEA of energy efficiency showed that, under the Constant Returns to Scale (CRS) model, 32% of units were fully efficient, while under the Variable Returns to Scale (VRS) model, 72% of units achieved full efficiency, with the remaining units considered inefficient to varying degrees. The optimization results of input use indicated that, in the VRS model, nitrogen fertilizer, manure, and agricultural machinery accounted for the highest energy-saving potential, with 14.97%, 14.73%, and 10.47%, respectively. In the CRS model, agricultural machinery, diesel fuel, and manure represented the greatest potential for energy conservation, with 38.55%, 27.63%, and 22.38%, respectively. The economic analysis showed that, compared to conventional practices, variable costs in the optimized scenario decreased by 8.08%, and total production costs decreased by 6.39%. As a result, gross revenue increased by 7.76%, while net revenue (and consequently net return per hectare) increased by 10.38% compared to the conventional scenario.</p>