Diabetic kidney disease (DKD) onset and progression is a major cause of end-stage renal failure in diabetic patients, however, no practical method has been reported to predict the progression rate of renal function decline. Nine serum compounds are reported to associate with prognosis in type 1 diabetes patients; however, quantitative analytical methods for these compounds lacks. Herein, we developed a simultaneous quantitative method for 15 compounds, including Niewczas’s nine biomarker candidates, associated with renal function and its prognosis in kidney disease patients to achieve a prognostic method of renal function decline in DKD patients. This report describes the development and validation of a LC–MS/MS analytical method for 15 compounds of biomarker candidates using human plasma, serum, and urine as sample matrices. The analytes are N-acetyl-L-alanine, N6-acetyl-L-lysine, N-acetyl-L-serine, N-acetyl-L-threonine, phenyl sulfate, pseudouridine, N6-threonylcarbamoyladenosine, tryptophan 2-C-mannoside, tyrosine O-sulfate, creatinine, p-cresol sulfate, 4-ethylphenyl sulfate, indoxyl sulfate, N1-methyladenosine, and trimethylamine N-oxide. The Capcell Pak ADME-HR column was compared to several general columns and selected as the most suitable column for the simultaneous analysis of all 15 compounds. The proposed method was validated for selectivity, accuracy, precision, stability, dilution integrity, and parallelism. This report describes the suitability of the calibration ranges established and the actual sample concentrations of serum and urine from type 2 diabetic patients, as well as new findings on the unknown analyte levels of several compounds in these samples. The proposed method can be used to aid the development of prognostic methods for renal function decline in patients with DKD.