Summary: We present an efficient modern strategy for solving some well-known classes of uncertain integral equations arising in engineering and physics fields. The solution methodology is based on generating an orthogonal basis upon the obtained kernel function in the Hilbert space \(W_2^1 \left[a, b\right]\) in order to formulate the analytical solutions in a rapidly convergent series form in terms of their \(\alpha\)-cut representation. The approximation solution is expressed by \(n\)-term summation of reproducing kernel functions and it is convergent to the analytical solution. Our investigations indicate that there is excellent agreement between the numerical results and the reproducing kernel Hilbert space (RKHS) method, which is applied to some computational experiments to demonstrate the validity, performance, and superiority of the method. The present work shows the potential of the RKHS technique in solving such uncertain integral equations.