The construction industry is a vital sector in Rwanda's economic development, but it faces challenges related to project performance, including delays and cost overruns. This study explores the effects of automated project task scheduling on construction project performance, with a specific focus on Better Design and Construction Limited in Rwanda. The objective is to investigate how the implementation of automated scheduling software influences efficiency, accuracy, resource allocation, and overall project management in the Rwandan construction context. The study focused on: project task scheduling on performance of construction projects in Rwanda. In this study, the theoretical orientation covered Resource Based View Theory. The study adopted a descriptive survey design. The target population of the study were the 161 respondents dealing with the projects at Better Design and Construction Ltd. Census approach was adopted in this study. The study used both primary and secondary data, where questionnaires were used for data collection. Cronbach's alpha test was utilized in assessing reliability of research instrument. Data collected was analyzed through SPSS version 21. Data analysis involved statistical computations for averages, percentages, and correlation and regression analysis. Descriptive statistics and Correlation (using the Karl Pearson's coefficient of correlation) were used to analyze the data and establish the relationship between the dependent variables and the set of independent variables. Qualitative data was analyzed through thematic analysis and presented in narrative form and verbatim citations. The unstandardized coefficients: The unstandardized coefficients represent the direct impact of the independent variable on the dependent variable without taking into account the scale or units of measurement. In this case, the constant (B = 0.017) suggests a minimal effect on the "Performance of construction projects." The small standard error (Std. Error = 0.222) indicates that this effect is relatively uncertain or imprecise. In contrast, the independent variable "Automated Project task scheduling" has a substantial impact with a high unstandardized coefficient (B = 0.999), suggesting a strong relationship with the "Performance of construction projects." The small standard error (Std. Error = 0.049) means that this effect is estimated with greater precision. In conclusion, the study's robust statistical analysis demonstrates that the implementation of automated project task scheduling has a substantial and statistically significant positive impact on enhancing the performance of construction projects, underlining the importance of adoptingThe Strategic Journal of Business & Change Management.