While technology investments in education have risen dramatically during the last decade, research has demonstrated multiple cases for oversold and underused technology tools that have failed to enhance teaching and learning. It is argued that teacher concerns play an important role in successful technology adoptions in schools. The purpose of this nonexperimental, correlational study was to examine teacher concerns regarding a Learning Management System (LMS) utilizing the Concerns Based Adoption Model (CRAM) conceptual framework. A sample of 345 Cypriot secondary teachers working in the seven pilot School-Net schools completed the Stages of Concern Questionnaire (SoCQ 075). Teacher Peak (most intense) concerns were examined with regards to selected demographic and technographic characteristics. Descriptive statistics indicated that the majority of teachers exhibited Peak concerns in Stages 0 (Unconcerned), 1 (Informational), and 6 (Refocusing); that is, they were unaware about the LMS innovation, requested fundamental information, and were skeptical about the LMS adoption. Pearson's chi-square test revealed that prior experience with instructional LMSs use was the variable most strongly associated with teacher Peak concerns (χ²(3) = 248.882, p < .001). The results from the logistic regression analysis revealed five significant predictor variables, out of 12 predictors, that could predict the dichotomous outcome variable of teacher Peak concerns based on the Lower (Stages 0, 1, 2, 3) and Higher (Stages 4, 5, 6) classification. The significant predictor variables were: (a) age (e^β = .994, p < .001), (b) specialization/content area ( e^β = .851, p = .002), (c) gender (e^β = .891, p = .005), (d) training on the instructional LMSs use (e^β = .737, p <.001), and (e) length of training on instructional technology use of more than six months (e ^β =1.182, p = .004). The predictive model significance was calculated using the chi-square test, χ² (6) = 123.23, p < .001, and the calculated correct classification was 87%. The model's explanation was computed using Nagelkerke's statistic, R ² = .462.The findings can be used to design need-specific professional development interventions for the effective LMS adoption in schools. Qualitative and longitudinal investigations are recommended for follow-up research.