Pretreatment is an essential step for breaking the recalcitrant structure of lignocellulosic biomass and allowing conversion to high-value-added chemicals. In this study, coconut fiber was subjected to three pretreatment methods to compare their impacts on the biomass’s structural characteristics and their efficiency in fractionating the biomass. This comparative approach was conducted to identify mild biomass pretreatment conditions that efficiently extract lignin and recover cellulose-rich pulp for the production of bioproducts. To this end, autohydrolysis, alkaline, and organosolv pretreatments were performed under different experimental conditions, and the physicochemical properties of the samples were evaluated using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), and chemical characterization of the cellulose, hemicellulose, and lignin fractions. Therefore, efficient experimental conditions were identified to pretreat coconut fibers with an extended understanding of the methods to process lignocellulose. Great delignification efficiency and pulp yield were obtained with organosolv > alkaline extraction > autohydrolysis under the selected conditions of 2 h at 185 °C in the presence of a catalyst, namely, 0.5 M NaOH, for 2 h at 55 °C and 20 min at 195 °C, respectively. FT-IR revealed a predominance of hydroxyl groups in fibers obtained from alkaline and organosolv pretreatment, showing higher lignin degradation and cellulose concentration in these samples. TGA revealed mass loss curves with similar behaviors but different patterns and intensities, and MVE analysis showed differences on the surfaces of each sample. The comparison of experimental parameters allowed the identification of suitable conditions for each extraction method, and structural analyses identified the specific characteristics of the fibers that could be obtained according to the method used. Therefore, the results are of great importance for developing sustainable and effective industrial processes.