In many studies, kinetic parameter estimation from spectroscopic data is performed with the absorbing species known beforehand, as this provides a straightforward link between the reaction models to the spectroscopic data. In practice, however, the absorbing species are generally unknown and they are only estimated based on professional experience and prior knowledge of the kinetic reaction. In this work, we propose an optimization strategy with both continuous and discrete decision variables in order to estimate kinetic parameters from spectroscopic data with unknown absorbing species. Also included in our approach is an estimability analysis for kinetic parameters based on the Gram-Schmidt orthogonalization procedure, along with covariance estimation. Four case studies were considered, which demonstrate the effectiveness of our approach. The first and second have simulated data and illustrate our approach with known solutions. The third and fourth are based on actual experiments from spectroscopy data sets. (c) 2018 American Institute of Chemical Engineers AIChE J, 64: 3595-3613, 2018