The thesis of this dissertation is that automating domain remodeling in AI planning using macro operators and making remodeling more flexible and applicable can improve the planning performance and can enrich planning. In this dissertation, we present three novel ideas: (1) we present an instance-specific domain remodeling framework, (2) we recast the planning domain remodeling with macros as a parameter optimization problem, and (3) we combine two domain remodeling approaches in the instance-specific remodeling context.