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Recent experimental observations of current blockades in 2-D material quantum-dot platforms have opened new avenues for spin and valley-qubit processing. Motivated by experimental results, we construct a model capturing the delicate interplay of Coulomb interactions, inter-dot tunneling, Zeeman splittings, and intrinsic spin-orbit coupling in a double quantum dot structure to simulate the Pauli blockades. Analyzing the relevant Fock-subspaces of the generalized Hamiltonian, coupled with the density matrix master equation technique for transport across the setup, we identify the generic class of blockade mechanisms. Most importantly, and contrary to what is widely recognized, we show that conducting and blocking states responsible for the Pauli-blockades are a result of the coupled effect of all degrees of freedom and cannot be explained using the spin or the valley pseudo-spin only. We then numerically predict the regimes where Pauli blockades might occur, and, to this end, we verify our model against actual experimental data and propose that our model can be used to generate data sets for different values of parameters with the ultimate goal of training on a machine learning algorithm. Our work provides an enabling platform for a predictable theory-aided experimental realization of single-shot readout of the spin and valley states on DQDs based on 2D-material platforms.