In the ratiometric fluorescent (RF) strategy, the selection of fluorophores and their respective ratios helps to create visual quantitative detection of target analytes. This study presents a framework for optimizing ratiometric probes, employing both two-component and three-component RF designs. For this purpose, in a two-component ratiometric nanoprobe designed for detecting methyl parathion (MP), an organophosphate pesticide, yellow-emissive thioglycolic acid-capped CdTe quantum dots (Y-QDs) (analyte-responsive), and blue-emissive carbon dots (CDs) (internal reference) were utilized. Mathematical polynomial equations modeled the emission profiles of CDs and Y-QDs in the absence of MP, as well as the emission colors of Y-QDs in the presence of MP separately. In other two-/three-component examples, the detection of dopamine hydrochloride (DA) was investigated using an RF design based on blue-emissive carbon dots (B-CDs) (internal reference) and N-acetyl L-cysteine functionalized CdTe quantum dots with red/green emission colors (R-QDs/G-QDs) (analyte-responsive). The colors of binary/ternary mixtures in the absence and presence of MP/DA were predicted using fitted equations and additive color theory. Finally, the Euclidean distance method in the normalized CIE XYZ color space calculated the distance between predicted colors, with the maximum distance defining the real-optimal concentration of fluorophores. This strategy offers a more efficient and precise method for determining optimal probe concentrations compared to a trial-and-error approach. The model's effectiveness was confirmed through experimental validation, affirming its efficacy.