This empirical study delves into the intricate factors that shape firms' choices regarding the adoption of robots within the Spanish context. Using a dataset encompassing a diverse set of industries, we employ an empirical analysis to uncover the determinants of robot adoption and investigate the associated outcomes on market variables. Our findings reveal several key factors that significantly influence a firm's likelihood of adopting robots. We find that firm profitability, exporter status, the control variables including share of R&D, and capital intensity exhibit strong positive relationships with robot adoption. Conversely, the impact of the level of human capital on adoption decisions is less pronounced. Furthermore, our study explores the impact of robot adoption on firm performance. We observe that firms embracing robotisation experience notable improvements in the output, exporting activities, and reduction in labour cost share. This study incorporates a gradient boosting-based machine-learning model, specifically XGBoost, along with instrumental variable regression models, to conduct rigorous robustness analyses and validate the obtained results. These findings contribute to the understanding of the dynamics and implications of robot adoption in the manufacturing sector, explaining the factors that drive firms' decisions and the subsequent market effects