This study is driven by a bid to generate a customer performance prediction model that may be of paramount importance to optimize sales for Castel Malawi within the Nkhatabay district, which has such erratic sales patterns. The research takes issue with the inconsistency of customer performance, making setting targets and overall strategic planning complicated for Castel Malawi. Guided by Ajzen's Theory of Planned Behavior, the study explores a number of demographic, geographic, and behavioral factors that can affect customer performance. An analytical cross- sectional design with a sample size of 242 customers of Castel, determined by Yamane's formula, was used for this research in Nkhatabay. The participants for this study were chosen from urban and rural areas using stratified random sampling. In this study, the data collection tool was a structured questionnaire. Analysis of data was done with the help of SPSS; descriptive and inferential statistical techniques were employed in developing the prediction model. The results show that education level, house ownership, and ordering frequency have a significant influence on customer performance. Those customers with higher education levels, who owned houses, and frequently ordered exhibited superior performances. The customer performance classifying model-developed as good or poor customers-presents valuable insights into factors affecting customer behavior and sales performance. This predictive modeling is going to be applied to assist Castel Malawi in better forecasting market demand and thus adjust its sales accordingly. With the use of insights from this research, Castel Malawi is going to improve the consistency of sales, hit targets, and enhance strategic planning within Nkhatabay district. The research fills a void in localized predictive modeling for customer performance, and such findings help in practical tools for optimality in sales within a competitive market.