Background/Context: Most students with disabilities receive the majority of their instruction in general education classrooms. Yet, general education teachers persistently describe feeling unprepared to academically support students with disabilities in those spaces. Because disabled students are typically excluded from mathematics education research, and because special education researchers typically describe mathematics teaching and learning in ways that are incongruent with ambitious mathematics instruction, there is arguably a lack of guidance for these teachers. In the absence of clear guidance, teachers may turn to the well-established mathematical ability hierarchy, which positions disabled students (among others) as less capable. Purpose/Objective/Research Question/Focus of Study: The purpose of this study was to uncover teachers’ talk about the mathematical capabilities of students with (and without) disabilities. Existing coding schemes (perhaps inadvertently) treat teachers’ views as uniform across students despite evidence that teachers hold different views of different students, in part because of the multiple and varied identities that students bring to the classroom. By using an adapted interview protocol, which yielded more (and more nuanced) analytic categories, I foregrounded students’ disability status as a factor that could relate to differences in teachers’ conceptions of who they view as mathematically capable. Research Design: I interviewed general education mathematics teachers ( N = 20) about their students ( n = 407) using an adapted version of Jackson et al.’s (2017) semi-structured protocol that focused on uncovering teachers’ usages of diagnostic and prognostic frames. I used open and concept coding to develop an expanded version of Jackson et al.’s coding scheme and then applied the new coding framework to the entire data set. I used student demographic data to compare within-group percentages, noticing to what degree students with disabilities were represented within particular qualitative categories in relation to their representation within the entire data set. I also used transformed data to estimate two multinomial logistic regressions: one that used diagnostic frames as the outcome variable, and one that used prognostic frames as the outcome variable. Both models used students’ disability status and teacher dummy codes as predictor variables. Conclusions/Recommendations: The majority of teachers in this sample explained mathematical struggle in unproductive terms and said they would aim instructional adjustment at unproductive outcomes for students with and without disabilities. However, students with disabilities were overrepresented in unproductive categories and underrepresented in productive categories in relation to both diagnostic and prognostic frames. Regression analyses indicated that a student was statistically less likely to get a productive diagnostic or prognostic frame if they had a disability label. Findings from this study highlight the necessity of including teachers’ views of their students’ mathematical capabilities in instructional improvement efforts. Second, they indicate that student-level factors, such as disability status, relate to qualitatively and quantitatively meaningful differences in teachers’ views of their students, suggesting the importance of attending to broader narratives around constructs that may be associated with teachers’ views, and the subsequent enactment of those views, in mathematics instruction.