This Background: The preservation of digital forensic evidence in cloud environments presents significant challenges for law enforcement agencies in developing economies. While cloud-based encryption tools offer potential solutions, adoption remains low due to misalignment between technology capabilities and operational task requirements. Objective: To examine the role of Task-Technology Fit (TTF) in predicting the adoption of cloud-based encryption for digital forensic evidence preservation, and to identify the specific task characteristics and technology features that influence forensic practitioners' adoption decisions. Methods: A multiphase mixed-methods design, embedded within a Design Science Research (DSR) framework, combined a needs-assessment survey of 91 Kenya National Police Service (KNPS) and judicial practitioners with the development and evaluation of a cloud-based encryption prototype (AES-256-GCM, RSA-3072, immutable audit logs). Task-Technology Fit was operationalized as a discrepancy index between independently rated task-characteristic importance and technology-characteristic capability to reduce common-method bias. Quantitative data were analysed using descriptive statistics, ANOVA, Pearson correlations, and multiple linear regression. Qualitative open-ended responses underwent reflexive thematic analysis and were integrated with quantitative findings via a joint display. Usability testing (n=30) and a 30-day pilot deployment (n=20, no control group) evaluated the tool's operational fit. Results: Current practices showed a procedural-technical gap: chain-of-custody logging (M=3.91/5) was adequate, but encryption use (M=3.08) and integrity hashing (M=2.63) were weak. Task-Technology Fit, operationalized as a discrepancy-based index, was the strongest predictor of adoption readiness (?=0.41, p<.001), explaining 38.7% of variance in adoption intentions. Judicial admissibility requirements (M=4.45) and chain-of-custody standards (M=4.38) were rated as the most critical task characteristics; encryption speed (M=4.12) and audit logging completeness (M=4.05) were rated as the most important technology characteristics. In laboratory and field evaluation, the prototype achieved 12–15% encryption overhead with zero errors over 9,000+ operations, a System Usability Scale score of 78.4 ("Good"), 30% faster task completion (Cohen's d=1.61), and was associated with an increase in encryption-log adoption from 18% to 72% over a 30-day pilot (?²(1)=28.6, p<.001) without a control group. Qualitative findings indicated that the fit–adoption relationship is further shaped by infrastructure constraints, training gaps, and particularly among judiciary staff institutional trust in courts' acceptance of digitally secured evidence. Conclusion: Task-Technology Fit is a useful framework for understanding cloud-based encryption adoption in this forensic context, though the cross-sectional, single-country, controlled-comparison-free design means these findings should be read as associations consistent with TTF theory rather than causal proof. Achieving fit in practice appears to require not only technical alignment with task requirements but also infrastructural investment, training, and engagement with judicial stakeholders whose adoption concerns are only partly explained by perceived technical fit.