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To study the relationships between stable C and N isotope compositions, C and N concentration of different organs during different growth stages and rice yield and quality under different irrigation regimes, experiment was conducted in the Key Laboratory of Efficient Irrigation-Drainage and Agricultural Soil Water Environment in Southern China, Ministry of Education, Nanjing, China, from May to October in 2013. Five treatments, including alternate flooding and light drought stress during tillering stage (T-LD), alternate flooding and heavy drought stress during tillering stage (T-HD), alternate flooding and light drought stress during jointing stage (J-LD), alternate flooding and heavy drought stress during jointing stage (J-HD) as well as control treatment (CK) with water depth being kept at 5 cm during the whole growth stage, were set up. Results indicated that rice yield had significant postive relationships with δ13C of root, stem and leaves of rice plants during rice ripening stage （P<0.05);the gross protein content of rice grains as well as chalky rice rate and chalkiness had significant relationships with δ15N of root, stem and leaves during jointing stage as well as ripening stage （P<0.05). The principal component analysis (PCA) was conducted for combination of the selected C and N related parameters, and the retained principal components (PCs) were used in stepwise regression with yield and quality parameters. PCA results showed that a maximum of 90.5% of the total variability in C and N related parameters was explained by the first eight PCs. The stepwise regression analysis indicated that C and N related parameters of different organs during different growth stages could explain 89%, 62%, 80%, 86%, 86% and 68% of total variance in rice grain yield (GY), gross protein content (GPC), brown rice rate（BRR）, chalky grain rate （ChGR）, chalkiness degree（ChD）and amylose content (AC), respectively. Results indicated that the selected C and N related parameters of different organs during jointing and rice ripening stages could accurately predict yield and quality of rice plant grown under different irrigation regimes．