pared v0.1.0 This release provides a citable archived version of pared, an R package for Pareto-based model selection using multi-objective optimization. pared is designed for model-selection settings in which users wish to balance multiple criteria, such as goodness-of-fit, sparsity, shrinkage, smoothness, structural similarity, and computational cost. The package provides a generic interface for user-defined multi-objective model-selection problems, together with built-in convenience wrappers for elastic net, fused lasso, fused graphical lasso, and group graphical lasso. The optimization routine uses Gaussian-process-based multi-objective optimization to approximate the Pareto front, and the package provides interactive two- and three-dimensional visualizations to help users inspect trade-offs among candidate models. Main functionality Generic Pareto-based model-selection interface through pared_optimize(). Support for user-defined objective functions, objective names, and objective directions. Built-in wrappers for elastic net, fused lasso, group graphical lasso, and fused graphical lasso. Interactive visualization of Pareto-optimal model-selection trade-offs. Examples demonstrating direct use with custom objectives and objective-space preferences. Simulation and case-study examples illustrating variable-selection and network-selection workflows. Software availability The development repository is available at: https://github.com/priyamdas2/pared This release corresponds to the software version archived for reproducible use with the revised Bioinformatics Advances manuscript.