Objectives: The objective of this study was to evaluate the potential of MIR to predict micronutrient status while reanalyzing archived soil (n=1649) samples after long-term storage (40 years). Methods: The infrared spectra of the samples collected from 30 countries from across the world were recorded between 4000-600 cm -1 wavelength range. 10 % of the samples were measured for Cu, Mn, Mo, Zn, B, Pb, Co, and Fe using the conventional wet chemistry reference methods. A modified partial least squares method with cross-validation is being used to develop calibration models for prediction of micronutrient properties of the samples from their spectra. Results: The micronutrients were in a wide range: Cu (0.03 100), Mn (0.9 378), Mo (0.007 3.6), Zn (0.09 185), B (0.06 10), Pb (0 38), Co (0 421), and Fe (0 445) showing significant differences in the micronutrient contents of the different soils. The spectra of the samples were recorded between 4000-600 cm range. A modified partial least squares method with crossvalidation will be used to develop calibration models for prediction of micronutrient properties of the samples from their spectra. Predictive models based on MIR spectra are under development for all properties. Conference Abstract Nyambura et al.; EJNFS, 5(5): 751-752, 2015; Article no.EJNFS.2015.268 752 Conclusions: Predictive models based on MIR spectra for all soil micronutrients can be used to predict a number of soil properties and it has potential to bridge the gaps in the data. © 2015 Nyambura et al.; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.