The selective and accurate determination of metal ions, crucial in various physiological processes within the human body, is of paramount importance, particularly when these ions, such as Fe(III), coexist with others in the sample. The manuscript addresses the challenge of determining Fe(III) selectively in the presence of interfering species. To achieve this, carbon dots (CDs) are employed as photoluminescence probes due to their biocompatibility and low cytotoxicity. The chemometric analysis of photoluminescence (PL) data was used to overcome selectivity challenges associated with CDs. This study utilized fluorescence excitation-emission matrices (EEMs), considered as second-order data, and applied unfolded partial least squares followed by residual bilinearization (U-PLS/RBL) to account for uncalibrated species.The developed model methodology was assessed using spiked samples containing uncalibrated and interfering species, namely Al(III), Pb(II) and Ni(II), at different concentration levels. The achieved limits of detection (LOD) and quantification (LOQ) at 0.02 and 0.06 mmol/L, respectively, highlight the high sensitivity of the approach. Notably, the application of one RBL component significantly reduces RMSEP values in samples spiked individually with each uncalibrated and interfering species, demonstrating the methodology’s effectiveness in overcoming strong interactions with CDs. Interestingly, this reduction was not observed in test samples containing only Fe(III), where optimal results were achieved without the application of the RBL component.This study introduces a novel approach by formulating a selective methodology for the determination of Fe(III) in the presence of interfering species, employing carbon dots (CDs) as photoluminescence probes. The application of chemometric analysis, specifically U-PLS/RBL, to mitigate selectivity challenges, coupled with the demonstrated sensitivity characterized by low LOD and LOQ values, emphasizes the scientific significance of this research. The results highlight the practical viability of the methodology, particularly in complex samples, contributing valuable insights to the field.