The objective of the present study is to develop robust statistical models for the prediction of critical diesel properties such as cloud point, pour point, and cetane index with composition inputs such as n-Paraffins, Iso-paraffins, Naphthenes, and Aromatics (PINA) obtained by flow modulated two-dimensional gas chromatography with flame ionization detection (GCXGC-FID). A single gas chromatographic measurement coupled with models to predict the key physical properties is attractive for refiners to make quick decisions in optimizing diesel blending. We present a partial least-squares (PLS) linear regression statistical model that has been developed using 41 data sets of diesel samples with different compositions, out of which 33 samples were used for the calibration and eight samples for validation of the model. The R-2 values obtained for cloud point, pour point, and cetane index were 0.92, 0.93, and 0.92 with standard deviations of 1.20, 1.50, and 0.40, respectively. The average relative errors for predicted values of cloud point, pour point, and cetane index are found to be 0.86, 1.02, and 0.25, respectively. The PINA analyses of diesel and kerosene samples were carried out using flow modulated GCXGC with flame ionization detection (FID). The technique adapts reverse phase gas chromatography with two capillary chromatographic columns; the columns differ in length, diameter, stationary phase, and film thickness to get maximum peak resolution. The gravimetric blends of high purity reference standards of paraffins, naphthenes, and aromatic compounds (PINA) with variable carbon numbers were used for identification and to draw the boundaries for group types. Monoaromatic and polyaromatic content obtained for diesel and kerosene samples by the flow modulated GCxGC method were comparable to the results obtained by the High Performance Liquid Chromatographic (HPLC) method as per IP 391 or ASTM D 6591. Repeatability and reproducibility of the GCxGC analysis were performed for several samples to validate the method. It has been found that the HPLC method for the determination of aromatics content using a single calibration standard for each type, such as mono-, di-, and polyaromatics, causes a small error in the quantification in some of the samples as the refractive indices of all the aromatic species present in the diesel and kerosene samples vary depending on the addition of alkyl side chains; the presence of heteroatoms such as sulfur, nitrogen, and oxygen; etc.