Financial Forecasting and Profitability of the Top 100 SMEs in Kenya
| dc.contributor.author | Mwanzi, James Munyalo | |
| dc.contributor.author | Jagongo, Ambrose | |
| dc.contributor.author | Makori, Daniel | |
| dc.date.accessioned | 2026-02-02T11:56:41Z | |
| dc.date.available | 2026-02-02T11:56:41Z | |
| dc.date.issued | 2025-12 | |
| dc.description | Research Article | |
| dc.description.abstract | Small and Medium Enterprises constitute critical economic drivers in developing economies, yet their profitability remains volatile despite contributing approximately 24% to Kenya's GDP and employing over 93% of the active labor force. This study examined the effect of financial forecasting on the profitability of the Top 100 SMEs in Kenya. An explanatory research design under positivist philosophy was adopted, employing a census approach that selected 40 consistently listed firms from the Top 100 SMEs ranking. Data were collected through questionnaires for primary information and audited financial statements for secondary data, then analyzed using SPSS with linear regression analysis. The results showed that financial forecasting had a statistically significant positive effect on profitability (β = 2.10, p = 0.027), meaning a one-unit improvement in forecasting increased profitability by 2.10 units. With R = 0.36 and R² = 0.13, the model indicated a moderate relationship where forecasting explained 13% of profitability variation, leading to the rejection of the null hypothesis at the 0.05 level. The study concludes that financial forecasting serves as a statistically significant determinant of profitability among Kenya's Top 100 SMEs, with effective forecasting enabling enterprises to predict cash flow fluctuations, manage liquidity prudently, and identify profit-enhancing opportunities. The study recommends that the Kenya MSME Authority should develop standardized financial forecasting training programs targeting SME managers to enhance predictive accuracy and implementation, the Kenya Association of Manufacturers should establish forecasting benchmarking frameworks enabling SMEs to compare practices against industry standards, financial institutions should integrate forecasting capability assessments into credit evaluation processes while providing technical support to borrowers and policymakers should mandate periodic forecast reviews and documentation for SMEs seeking government support programs to institutionalize strategic financial planning practices that demonstrably improve profitability outcomes. | |
| dc.identifier.citation | Mwanzi, J. M., Jagongo, A., & Makori, D. (2025). Financial Forecasting and Profitability of the Top 100 SMEs in Kenya. Journal of Finance and Accounting, 9(6), 27-45. https://doi.org/10.53819/81018102t5402 | |
| dc.identifier.issn | 2616-4965 | |
| dc.identifier.uri | https://ir-library.ku.ac.ke/handle/123456789/32228 | |
| dc.language.iso | en | |
| dc.publisher | Stratford Peer Reviewed Journals and Book Publishing | |
| dc.title | Financial Forecasting and Profitability of the Top 100 SMEs in Kenya | |
| dc.type | Article |