In this paper, we present "SMKA18" analysis which is a first attempt to extract the set of nextto-next-leading-order (NNLO) spin-dependent parton distribution functions (spin-dependent PDFs) and their uncertainties determined through the Laplace transform technique and Jacobi polynomial approach. Using the Laplace transformations, we present an analytical solution for the spindependent Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equations at NNLO approximation. The results are extracted using a wide range of proton g p 1 (x, Q 2 ), neutron g n 1 (x, Q 2 ) and deuteron g d 1 (x, Q 2 ) spin-dependent structure functions dataset including the most recent high-precision measurements from COMPASS16 experiments at CERN which are playing an increasingly important role in global spin-dependent fits. The careful estimations of uncertainties have been done using the standard "Hessian error" propagation. We will compare our results with the available spin-dependent inclusive deep inelastic scattering dataset and other results for the spin-dependent PDFs in literature.The results obtained for the spin-dependent PDFs as well as spin-dependent structure functions are clearly explained both in the small and large values of x.