Invasive species are top contributors to biodiversity loss and pose major threats to ecosystems. Biological invasions cost billions of dollars annually in damages and control efforts aimed at restoring ecological communities and conserving declining species. However, efforts to reduce invasive species often fail without a comprehensive understanding of how specific actions contribute to sustainable population control and recovery of native species. Predictive models are valuable tools for analyzing invasive species dynamics over time and can evaluate how specific management actions reduce invasive populations to support native species recovery. Channel Catfish (Ictalurus punctatus), a commonly introduced fish species in North America, have thrived as an invasive species in the San Juan River for decades despite mechanical removal efforts. Consequently, there is a need to assess Channel Catfish population dynamics in relation to removal efforts and identify new strategies for effective management. We used a statistical catch-at-age model to estimate changes in age-specific Channel Catfish abundance over three decades of mechanical removal efforts and to explore the effectiveness of potential alternative control strategies for reducing abundance. Our model revealed substantial temporal variation in catfish abundance throughout the removal period, with a three-fold increase in the first 14 years, followed by a gradual decline when efforts were intensified. Gear selectivity was highest for larger fish, resulting in a shift in age structure towards smaller fish. Increased discharge and temperature marginally reduced recruitment. Future projections suggest that the intensity of current removal efforts would need to increase by at least 5x to reduce biomass to 15% of the current population within 10 years. While removal efforts have been effective in reducing biomass, achieving major and sustained reductions with current approaches would require substantially more effort. Future control projects should consider fitting population models as early as data are available to guide large-scale management efforts.