Chemical properties have been used as a way of following the composting process and compost maturity, however, their analysis is very time consuming as each must be separately determined. By developing a more rapid method to predict these properties, time and cost would be saved. This study investigates the use of Fourier Transform mid-Infrared Spectroscopy (FT-IR) for this purpose. FT-IR spectra and measured values of several chemical properties from a variety of compost mixtures were used to produce calibrated models using partial least-squares regression analysis which predicted the known chemical properties. These models displayed a range of accuracies that for most properties was more than sufficient to follow at least broad dynamic changes associated with maturation. The best calibrations were achieved for total C, total N, LOI, lignin, and cellulose with r2 values within the range 56-77%. Some degree of calibration was achieved for available-P and NH4+-N, with r2 values of between 40% and 57%. No useful calibration could be achieved for NO3- or pH.