The coefficient conjugate is often the subject of conjugate gradient techniques. In this work, we use the quadratic function to unconstrained optimization problems and construct an unique coefficient conjugate gradient method. Based on a novel coefficient conjugate, we provided a search direction and fascinating conjugate gradient approach. We demonstrate that, given the appropriate circumstances, the proposed technique is universally convergent. Our numerical findings show that this method is effective for unconstrained optimization problems.