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This paper proposes a new non-intrusive method for uncertainty quantification called Polynomial Chaos Decomposition with Differentiation (PCDD) that uses higher-order sensitivities of the response. In PCDD, the polynomial chaos expansion (PCE) of the response is differentiated with respect to the basis random variables using multi-indices. This differentiation results in a system of linear equations which can then be solved to determine the expansion coefficients. Here, the higher accuracy, Modified Forward Finite Difference (ModFFD) that involves representation of the response using Taylor expansion of order equal to the chaos-order is used in combination with PCE. Therefore, the total number of samples required with this method is equal to the number of terms in the PCE. To verify the validity of this new technique, two analytical problems and two stochastic composite laminate problems were studied. The …