Study area:Present study has been conducted in the south- east region of Bangladesh. Multistage sampling technique has used to select the study area. In the first stage, Khulna District has been chosen for purpose of the study from total of 64 districts in Bangladesh; because, this district is situated in the south-west region of Bangladesh. In the second stage, Dighalia Upazila, has been selected from Khulna Districts because most of the farmers in Dighalia Upazila are engaged in rice cultivation and fish cultivation. At the third step, Gazirhat Union has been selected purposively as the farmers in this area are engaged in both rice-fish farming and mono rice production under double cropping system all the year round. At the last stage, a total of 8 villages of the union have been selected randomly. Sampling and data collection:For study purpose, farmers who produce only rice and farmers who produce rice-fish have been considered as population. Existing literature survey and a pilot field survey confirm that double cropping system is in operational for rice cultivation in the study area. Generally, cropping season for Boro rice ranges from November to April and duration of Aman rice is June to September (Ahmed and Garnett, 2011; Ahmed et al., 2011; Hasanuzzaman et al., 2011). On the other hand, two widely practiced rice-fish cultivation systems are concurrent culture (integrated) – growing the fish together with the rice in the same area – and rotational culture (alternate) – where the rice and fish are grown at different times (Ahmed et al., 2011; Hasanuzzaman et al., 2011; Roy et al., 2013). Time frame for integrated rice-fish farming is July to November and December to April for Boro rice production. On the other hand, alternate rice-fish farming involves producing of fish in the monsoon from June to December and cultivation of Boro rice from November to April.In case of study area, quick field survey reveals that mono rice farmers produce Boro and Aman in two cropping season, on the other hand, most of the rice-fish farmers are practicing alternate culture due to the lack of enough water and fish prawn in the dry season. So, the samples of the present study include 30 mono rice farmers and 30 alternate rice-fish producing farmers from the time period of June 2015 to April 2016. The sample has been selected purposively for the study.For accomplishing the study, data have been collected from both primary and secondary sources. In order to collect primary data, well-structured questionnaire, pretested and revised on the basis of findings and experiences originated at the time of pilot survey has been used. Primary cross-section data have been collected through questionnaire survey at the time of final field survey. Besides, necessary secondary data have been collected from published book, journals, working papers, internet etc. Data analysis and model specification: In order to analysis data, some mathematical tools have been applied in the study. Profit function has been used to identify the net profit of the farmers from mono rice and rice-fish cultivation, and a Cobb-Douglas production function has been applied to estimate the production efficiency of rice-fish farming and mono rice farming in association with measuring the returns to scale from both production function. The description of the variables used has been mentioned with measurement unit. Hypothesis testing:This study intends to find out the economic difference between mixed rice-fish and mono rice farming in the study area. For this reason, a research hypothesis has been articulated as given below: Null Hypothesis: H0 = There is no difference between mixed rice-fish and mono rice farming in terms of economic returns. Alternative Hypothesis: H1 = There is economic difference between mixed rice-fish and mono rice farming in terms of economic returns. For data analysis, a number of computer software have been used. At first, collected primary data have been organized and stored by MS Excel 2016. In the second step, mathematical and statistical calculations have been compiled through using STATA 12 and IBM SPSS Statistics 20.