SCOPE (Symmetric COvariance Population Estimator) is a hierarchical Bayesian regression framework implemented in R and Stan. It fits a linear scaling relation between two observed quantities while fully accounting for measurement uncertainties in both variables, including asymmetric uncertainties modelled via a skew-normal approximation. The regression slope is derived from the intrinsic population covariance (beta = rho * sigma_y / sigma_x), treating both variables symmetrically during fitting. The method is designed for astrophysical scaling relations but is applicable to any two-variable relation with measurement uncertainty in both coordinates.