  In this paper, we present {\tt SMKA18} analysis which is a first attempt to
extract the set of next-to-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
spin-dependent Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equations
at NNLO approximation. The results are extracted using a wide range of proton
$g_1^{p}(x, Q^2)$, neutron $g_1^{n}(x, Q^2)$ and deuteron $g_1^{d}(x, Q^2)$
spin-dependent structure functions dataset including the most recent
high-precision measurements from {\tt 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 $x$.
