Curriculum-based measurements (CBM) are used in schools to screen students for academic difficulties. Oral reading fluency curriculum-based measures (CBM-R) are the most popular, yet several studies have identified predictive bias in CBM-Rs in relation to key variables (e.g., race, sex). Despite a massive increase in the use of these measures as screeners, studies of predictive bias have not been conducted recently, and studies have not quantified how predictive bias may affect decisions about students. The present study used moderated multiple regression (MMR) to investigate if predictive bias was present in third (n = 484) and fifth (n = 460) grade student CBM-R data as tied to key demographic variables (e.g., sex, ethnicity/race, socio-economic status). From the analyses of third grade data, slope bias was identified in relation to sex. CMB-Rs predicted Kansas Assessment Program English Language Arts exam (KAP ELA) scores slightly better for girls than for boys. Ethnicity/race and lunch status led to statistically significant intercept bias. White students' predicted KAP ELA reading scores were underestimated by CBM-Rs while African American and Hispanic students' predicted KAP ELA reading scores were overestimated by CBM-Rs. Predicted scores of students paying for lunch were underestimated. Predicted scores of students receiving free/reduced lunch were overestimated. From the fifth grade analyses, slope bias was found for ethnicity/race. CBM-Rs predicted KAP ELA reading scores better for White students than for African American students. Lunch status also led to statistically significant intercept bias. Predicted scores of students paying for lunch were underestimated while predicted scores of students receiving free/reduced lunch were overestimated. Next, this study determined how many students were affected by predictive bias by comparing the number of students identified as non-proficient readers by common and group specific regression equations and cut scores. When group optimal cut scores were used versus a common cut score, the number of White third grade students identified decreased by 37%, but the number of Hispanic and African American students identified remained the same. When group optimal cut scores were used, the number of high SES third grade students identified decreased by 38%, while the number of low SES third students identified increased by 20%. For fifth grade students, the number of high SES students identified decreased by 27% while the number of low SES students identified increased by 16%. The practical implication of these findings is that when students are screened, some are either not receiving the necessary services or are wrongly receiving unnecessary services based on group status. As a screening tool, CBM-Rs need to be reviewed within the context of educational decision-making processes to safeguard against misidentification and to ensure proper provision of services. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]