As a method to improve the design prediction accuracy by utilizing integral experimental data, the conventional cross-section adjustment method (CA) based on Bayes the- orem is widely used. On the other hand, propositions of the generalized bias factor method (GB) in 2006 and the extended bias factor method (EB) in 2007 have stimulated theoretical study in this field. Subsequently, several new cross-section adjustment methods were proposed: the ex- tended cross-section adjustment method (EA); the cross- section adjustment methods based on minimum variance unbiased estimation (MVUE), which include the MVUE- based rigorous EA (MREA) and the MVUE-based rigorous CA (MRCA); and the dimension-reduced cross-section ad- justment method (DRCA). In the present paper, we applied these methods to a real-scale problem of design prediction accuracy evaluation for a large-size sodium cooled fast re- actor and compared their performances. From these re- sults, we discuss a proper use of these design methods.