Soil samples analysis for carbon values are consistently being needed for the application of allometric equations in estimating below ground carbon stock. Unfortunately, current conventional laboratory analysis methods for quantifying soil carbon in soil samples are slow, expensive and time consuming. A rapid and inexpensive method has been successfully developed and tested particularly when dealing with large number of samples or when soil information is needed at landscape level. The objective of this study was to assess the applicability and the usefulness of the Mid Infrared spectroscopy to estimate soil carbon values in 192 soil samples collected across four types of land use systems (forest, Mixed cropping, fallow, Cocoa plantation)in the southern part of Cameroon. Soil carbon estimates obtained using conventional methods for a randomly selected sub-set of 58 (30%) samples were used for model calibration while the remaining (134) 60% were used for model validation. The laboratory results were calibrated to reflectance measurements using partial least square of regression (PLSR). A calibration model, with the equations developed using Principal Component Analysis and PLSR was developed on the samples for which laboratory analysis were obtained. The predictive ability of the PLSR model was assessed on predicted and measured values of soil attributes using the coefficient of determination (r2) and the root mean square error (RMSE). The results obtained from the calibration procedure inveterate the practicability of MIR in predicting soil parameters. Good calibrations (r2 = 0.92 and RMSP = 0.14; r2 = 0.94and RMSP = 0.13) were obtained for total Carbon and organic Carbon respectively. This indicated that the infrared spectra could explain 92% of organic Carbon (while ? 13% error) and 94% of Total Carbon (while ? 14% error). The study demonstrated and confirmed that the MIR-PLS method can be used to estimate soil carbon and other soil properties based on calibrations of MIR values. These results are highly encouraging and form the basis for developing regional scale frameworks for assessment and monitoring of soil carbon.