Purpose – This study aims to explore the strategic impact of R&D and export activity on the diverse dimensions of US manufacturing firms’ performance. It also explores, using a predictive analytic model, the interactive synergistic effect that R&D and exports have on firm performance. Design/methodology/approach – This study presents an innovative two-stage regression-neural network approach. Complementing conventional statistical analysis, the predictive backpropagation neural network explores the relative impact of R&D and exports and their synergistic effect on firm performance. Findings – This study demonstrates the significant and positive effect of R&D and export strategy/activity on the economic performance of leading US manufacturing firms, particularly on their market-based performance (i.e. sustained growth rate or SGR). Furthermore, this study finds that the synergistic effect of R&D and exports on short-term performance (i.e. return on investment) is positive in high-tech firms but negative in low-tech firms. However, the synergistic effect on SGR is increasingly positive regardless of the level of technology. Originality/value – In addition to traditional statistical analysis, this study uniquely investigates the relative importance of selected strategic variables, along with R&D and export activity and their differential synergistic effects, for firms’ economic performance in contrasting industry settings (high-tech vs low-tech)